Bank lån handel system and metoden

Banklån till handlare Anställd feb 2009 Status: Medlem 77 Inlägg Jag har tänkt mycket på det här eftersom jag har mycket lite av mina egna pengar (jag är på college just nu) Jag tycker inte att det är en dålig idé så länge du har en plan , sätta gränser, och har haft konsekvent framgång innan på en liten bit. Då är det bara en annan affärsbeslut och det kan betala sig. Nyckelordet är att konsekvent framgång har uppnåtts. Låt oss säga att du lånar 50 000. Inte handla hela saken på en gång. Börja med 10.000 och gör ett mål att få x och när du får det lägger du till lite mer och upprepar samma process tills du känner dig bekväm att handla hela acct. Om du är en halv anständig näringsidkare är räntan så liten jämfört med vinsten som det inte kommer att vara ett problem. Mest framgångsrika näringsidkare känner redan till sin maximala dragning, eller den punkt där de slutar handla eftersom systemtraderaren är klar. Låt oss säga det -20. Om du någonsin når -20 slutar du handla och betala av lånet. Om du antar att du hade några bra månader innan det här, borde det vara ungefär det nummer det började. Deras absolut ingen anledning att blåsa hela acct. Ett annat alternativ är att gradvis minska din positionsstorlek när du börjar förlora och öka när du börjar vinna. På det sättet kommer du aldrig att torka ut hela acct och kan betala av lånet om något inte fungerar. Detta är inte realistiskt för mig eftersom jag måste bevisa mig själv på en liten bit. Om du hoppar över detta steg är det garanterat misslyckande. Genom att göra det här sättet ger du dig själv möjlighet att bli bevisad fel och om du aldrig är, kan ett lån vara mycket fördelaktigt i början av din handel. Jag pratar om när du redan är en etablerad näringsidkare och vill köpa ett hus, en bilbåt. något. är det svårt att få ett banklån (när handel är din enda inkomst) Det är vad jag trodde du frågade om. Först av allt kommer du att klassificeras som egenföretagare. För en stund, här i staterna, var bankerna lite vänligare för egenföretagare. Nu har de återvänt till de tidigare, mer konservativa dagarna. Nu måste du bevisa din inkomst genom avkastning. Och banken gillar att se konsistens över de två åren. Om du ansöker i mitten av året eller senare, kommer du förmodligen att behöva ange dina nuvarande år P och L uttalande. Och att underteckna ett formulär som godkänner bankens tillgång till dina avkastningar. Med andra ord kan du inte lämna en avkastning med IRS och skicka en mer tilltalande till banken. De kan referera till den. Bankinlåning brukar inte heller göra det - bara skattedeklarationer. Ive varit egenföretagare i 30 år och var tvungen att hantera banker på alla sätt. Förra gången ville de ha bevis på företagsägarskap de senaste 5 åren. För några år sedan kunde jag låna något belopp inom förnuft, bara på en underskrift. Nu måste jag gräva trots att ingenting i min bokföring har förändrats. Om min egenföretagare kom helt och hållet från handel tror jag att det skulle bli ännu svårare. Bankerna är hungriga för kvalificerade låntagare just nu. quotQualifiedquot, vilket betyder superkreditpoäng, kontrollerbar inkomst för 2 år och liten nuvarande skuld. Även om du inte behöver ett lån just nu, ring upp en bank och förklara din situation. De ska låta dig veta i kort ordning eller inte du har en chans. Då kommer du veta vad du kommer att vara emot när du behöver ett lån. Bil lån är lite enklare. Du kan hitta finansbolag på nätet som specialiserat sig på auto lån och ger dig en exceptionell ränta baserad helt på din kreditpoäng och angivna intäkter, förutsatt att lånet står i proportion till bilens värde. Redigera: Jag har bara märkt dig från Norge så mycket av mitt inlägg kommer inte att tillämpas. Gör en affärsplan som omfattar 12 månaders detaljerade uttalanden, gå till bankinvesterare och gör en vinstdelning på 5050. På så sätt tar de alla risker. Jag känner någon som har gjort det här i Storbritannien och var inte bett att täcka några förloringar med säkrade lån etc. Med tanke på dagens klimat finner du det svårt men inte omöjligt. PS. Du kan även hitta mäklare sponsrar dig om de tycker att din metod är trovärdig på lång sikt. Hes inte försöker låna pengar för att handla. Han vill veta hur svårt det är för en näringsidkare att få ett lån för andra saker. Med andra ord, kommer en bank överväga att handelsinkomster ska vara tillförlitliga nog för att betala tillbaka ett lån för husbåt etc. System och metod för optimering av fast ränta Hela lånehandeln USA 20140188692 A1 Optimering av fast ränta för hela lånehandeln. Specifikt tillhandahåller uppfinningen datorbaserade system och metoder för att optimalt förpacka en befolkning av hela lån till obligationer i antingen en seniorbaserad obligationsstruktur eller i pooler av passera genom värdepapper garanterade av en statlig myndighet. Modeller för varje typ av obligationsstruktur bearbetas på lånpopulationen tills antingen en optimal bindningspaket hittas eller en användare bestämmer att en lösning med tillräcklig hög kvalitet finns. Dessutom kan modellerna ta hänsyn till bud för hela lån genom att allokera hela lån som uppfyller kravet på anbudet men som är minst gynnsamma för att bli värdepapperiserade. (25) Det som hävdas är: 1. En datorimplementerad metod innefattande: att med hjälp av en dator skapa en modell innefattande en objektiv funktion som representerar ett totalt marknadsvärde för den seniorabordinära bindningsstrukturen för flertalet lån och maximerar med hjälp av datorn objektivfunktionen för att maximera det totala marknadsvärdet av den seniorsubordinära bindningsstrukturen. 2. 2. Den datorimplementerade metoden enligt patentkrav 1. varvid steget att maximera objektivfunktionen innefattar att bestämma ett marknadspris på varje lån som bestämmer en första viktad genomsnittlig exekveringskupong för det antal lån som motsvarar marknadspriset för varje lån som bestämmer den totala marknaden värdet av den seniorsubordinerade strukturen vid den första vägda genomsnittliga exekveringskupongen, som detererar den viktade genomsnittliga exekveringskupongen och bestämmer ett totalt marknadsvärde för den seniorsubordinerade strukturen vid varje iteration och bestämmer den viktade genomsnittliga exekveringskupongen som har de högsta totala marknadsvärdena för den seniorbaserade strukturen. 3. Den datorimplementerade metoden enligt patentkrav 1. vidare innefattande att utveckla och maximera en objektiv funktion för att optimalt dela åtminstone ett av lånen i två pseudolån för att förhindra skapande av enbart intresseobligation eller en principiell bindning, varvid de två pseudolånen innefattar olika kupongvärden. 4. En datorimplementerad metod för att optimalt samla en befolkning av lån till pass genom obligatoriska pooler, varvid metoden innefattar: val av befolkning av lån som bestämmer, på datorn, ett optimalt genomförande av varje lån från befolkningen i lån genom en uppköp eller en köpa ned en garantiavgift som bestämmer en eller flera pooler för vilka varje lån är berättigat att bygga en modell baserad på minst en begränsning för minst en bestämd pool och fördela lån till en eller flera passera genom obligationspooler. 5. Den datorimplementerade metoden enligt patentkrav 4 innefattar vidare att bestämma, genom datorn, åtminstone en modul av en eller flera moduler som är konfigurerad för att poola populationen av lån till passera genom obligationspooler baserat på en mottagen ingång, varvid den åtminstone en modulen innefattar en genomgångsmodul. 6. 4. Den datorimplementerade metoden enligt patentkrav 4. där modellen innefattar en objektiv funktion innefattande en linjär kombination av ett marknadsvärde för varje befolkning av lån. 7. 7. Den datorimplementerade metoden enligt patentkrav 6. där allokering av lånen innefattar att exekvera modellen för att maximera objektivfunktionen. 8. Den datorimplementerade metoden enligt patentkrav 4. vidare innefattande att omvandla åtminstone en begränsning av varje passera genom bindningspoolen till en villkorlig begränsning. 9. Den datorimplementerade metoden enligt patentkrav 4. vidare innefattande att omvandla åtminstone en del av den åtminstone ena begränsningen av varje passera genom bindningspoolen till en villkorlig begränsning före bearbetning av modellen för att säkerställa att modellen är lösbar. 10. Den datorimplementerade metoden enligt patentkrav 4. vidare innefattande att omvandla var och en av de åtminstone ena begränsningarna till en villkorlig begränsning för att tillåta begränsningar att vara tillämpliga för att endast passera genom obligationspooler som tilldelas. 11. Den datorimplementerade metoden enligt krav 4, vidare innefattande att allokera åtminstone en av befolkningen av lån till en odelad pool. 12. Den datorimplementerade metoden enligt krav 4, vidare innefattande att tilldela lån till en odelad pool om var och en av passering genom obligationspooler inte kan fördelas med populationen av lån, där lån i den odelade poolen ges noll marknadsvärde och vari bearbetning av modellen Vidare innefattar det att minimera antalet lån som tilldelas den odelade poolen. 13. 4. Den datorimplementerade metoden enligt patentkrav 4. vari modellen beräknar begränsningen av var och en passerar genom bindningsbassängen och en utbetalning som är associerad med var och en passerar genom bindningspoolen. 14. Ett system innefattande: ett minne innefattande en uppsättning instruktioner för allokering av en del av ett flertal lån till ett lånepaket och en dator kopplad till minnet och konfigurerad att utföra uppsättningen instruktioner för att: bestämma vilken av de många lån som möts en eller fler begränsningar av lånepaketet bestämmer ett marknadspris på varje av de många lånen baserat på en värdepapperiseringsmodellmodell en objektiv funktion för att bestämma vilka lån i flertalet lån som uppfyller ett eller flera hinder är minst lönsamma för värdepapperisering i värdepapperiseringsmodell och fördela de lån som uppfyller en eller flera begränsningar och är minst lönsamma för värdepapperisering i lånepaketet. 15. 14. System enligt patentkrav 14. där värdepapperiseringsmodellen innefattar en seniorsubordinatmodell. 16. 14. System enligt patentkrav 14. där objektivfunktionen är modellerad för att minimera spridningen mellan ett vägat genomsnittligt pris på lånen i lånepaketet och en TBA-obligationspris på den vägda genomsnittliga kupongen av lånen i lånepaketet . 17. Systemet enligt krav 14, varvid den objektiva funktionen är modellerad för att minimera ett dollarvärde av en spridning mellan ett vägat genomsnittligt pris på lånen i lånepaketet och en TBA-obligationspris på den vägda genomsnittliga kupongen för lånen i lånepaketet. 18. En metod för att optimera fullräntahandel med fast ränta, varvid metoden innefattar: att välja en befolkning av lån som väljer att, via en dator, ett eller flera lån som uppfyller en begränsning av ett bud genom att bestämma ett pris för varje lån som uppfyller begränsning baserad på en värdepapperiserad modell som bestämmer om datorn ska använda en effektiv modell för att välja vilken av de ett eller flera lån som är minst gynnsamma för att vara värdepapperiserad och om den effektiva modellen används, väljer du, av datorn, vilken av Det en eller flera lånen är minst gynnsamma för att vara värdepapperiserat med minsta dollarvärde av spridningen. 19. 19. Förfarande enligt patentkrav 18. Vidare innefattande: att av datorn bestämma åtminstone en modul av en eller flera moduler som optimerar helränshandel med fast ränta baserat på en mottagen ingång, varvid den åtminstone en modulen innefattar en hel lånemodul. 20. 18. Förfarande enligt patentkrav 18. Vidare innefattande steget att allokera en del av flertalet hela lån till ett paket av hela lån för att sälja hela lån, varvid den del omfattar hela lån som uppfyller minst en begränsning och är mindre lönsam än de andra hela lånen när de görs till ett obligationslån i obligationsstrukturen om den effektiva modellen inte används, då väljer man av datorn vilken av de ett eller flera lån som är minst gynnsamma för att vara värdepapperiserad genom att minimera spridningen. 21. Ett system innefattande: en dator som är kommunikabelt kopplad till nätverket och konfigurerad att: skapa en modell som motsvarar ett flertal överskott av kupongbindningspooler och en oallokerad pool, varvid varje överskott av kupongbindningspool innefattar åtminstone en begränsning och bearbetar modellen för att allokera var och en av lånen till antingen en överskott av kupongbindningspoolen eller in i den odelade poolen för att maximera det totala marknadsvärdet för den överskjutande kupongen som tilldelas de överliggande kupongbindningspoolerna. 22. 21. System enligt patentkrav 21. där modellen innefattar en objektiv funktion som representerar det totala marknadsvärdet för den överskjutande kupongen som tilldelas till de överliggande kupongbindningspoolerna. 23. 21. System enligt patentkrav 21. varvid datorn är vidare konfigurerad att transformera var och en av de åtminstone ena begränsningarna till en villkorlig begränsning. 22. 21. System enligt patentkrav 21. där datorn är vidare konfigurerad att transformera var och en av de åtminstone ena begränsningarna till en villkorlig begränsning för att tillåta begränsningar att vara tillämpliga på endast överflödiga kupongbindningspooler som tilldelas. 24. 21. Systemet enligt patentkrav 21. där datorn är vidare konfigurerad att: identifiera de överskjutande kupongpoolerna för vilka var och en av lånen kan allokeras baserat på säkerheterna för lånen och kollapsa varje lån som identifierats för en överkupongkupong i ett enda lån till minska antalet lån i modellen. Denna ansökan är en delning av U. S. patentansökan Ser. Nr. 12533 ​​315, inlämnad den 31 juli 2009, vilket hävdar fördelen med den amerikanska provisoriska patentansökningen nr 61191 011, inlämnad 3 september 2009, vilka båda härmed helt häri införlivas som referens. Föreliggande uppfinning hänför sig i allmänhet till system och metoder för att optimera lånehandel och mer specifikt till datoriserade system och datorimplementerade metoder för att optimera paket av hela lån för utförande i obligationer eller försäljning som hela lånepaket. Finansinstitut, till exempel investeringsbanker, köper lån och låneportföljer från banker eller låntagare främst för att securitisera lånen i obligationer och sedan sälja obligationerna till investerare. Dessa obligationer betraktas som värdepappersbaserade värdepapper eftersom de är säkerställda av tillgångarnas tillgångar. Många typer av lån kan värdepapperiseras i obligationer, inklusive bostadslån, kommersiella inteckningar, billån och kreditkortsfordringar. En mängd obligationsstrukturer kan skapas från en befolkning av lån, där varje struktur har egenskaper och begränsningar som måste redovisas för att maximera den vinst som ett finansinstitut kan realisera genom att värdepapperiseras i obligationer. Den optimala grupperingen eller sammanslagningen av lån i obligationer för en viss obligationsstruktur och en viss lånepopulation kan bero på egenskaperna hos varje lån i befolkningen. Vidare kan obligationspolicyn eller exekutivkupongen som ett individuellt lån exekveras bero på obligationspolicyn eller bästa genomförandet av varje annat lån i befolkningen. Eftersom den typiska lånepopulationen för värdepapperisering i obligationer är mycket stor (t ex 10 000 lån eller mer) kan det vara utmanande att bestämma en optimal sammanslagning av lån för värdepapperisering i obligationer. Följaktligen behövs det system och metoder för att optimera förpackningen av en befolkning av lån till obligationer för en viss obligationsstruktur. Uppfinningen tillhandahåller datoriserade system och datorimplementerade metoder för att optimera fullräntahandel med fast ränta för en befolkning av hela lån. En aspekt av föreliggande uppfinning åstadkommer ett system för att optimera helränshandel med fast ränta. Detta system innefattar ett datorsystem som innehåller en programvara som innehåller en eller flera moduler som kan användas för att utveckla en modell för att bestämma en värdepapperiseringsstrategi för en befolkning av hela lån, värdepapperiseringsstrategin inklusive obligationer och operativ att bearbeta modellen till en optimal värdepapperiseringsstrategi för populationen av hela lån finns och ett användargränssnitt för att ta emot användarinmatning för en eller flera moduler och för att utföra den optimala värdepapperiseringsstrategin, användargränssnittet är i kommunikation med programvaran. En annan aspekt av föreliggande uppfinning åstadkommer en datorimplementerad metod för att bestämma en optimal exekveringsbindningskupong för varje lån i en grupp av lån i en seniorbaserad bindningsstruktur. Metoden innefattar att skapa en modell bestående av en objektiv funktion som representerar ett totalt marknadsvärde av den senarelaterade obligationsstrukturen för lånen. Vidare innefattar metoden maximering av objektivfunktionen för att maximera det totala marknadsvärdet för den seniorsubordinära bindningsstrukturen. En annan aspekt av uppfinningen tillhandahåller en datorimplementerad metod för att optimalt samla lån till passering genom obligationspooler. Metoden innefattar att välja en befolkning av lån. Vidare innefattar metoden för varje lån av urvalspopulationen av lån att ett optimalt genomförande av varje lån fastställs genom en uppköp eller en nedköp av garantiavgift. Vidare innefattar metoden bestämning av en eller flera pooler för vilka varje lån är berättigat. Dessutom innefattar metoden att bygga en modell baserad på minst en begränsning för minst en bestämd pool och allokering av lån till den en eller flera passera genom obligationspooler. En annan aspekt av uppfinningen tillhandahåller ett system innefattande ett minne som har en uppsättning instruktioner för allokering av en del av en grupp av lån till en lånepaket. Vidare innefattar systemet en dator kopplad till minnet. Vid genomförandet av uppsättningen instruktioner bestämmer datorn vilket av lånen som uppfyller en eller flera begränsningar av lånepaketet. Dessutom bestämmer datorn ett marknadspris för varje lån baserat på en värdepapperiseringsmodell. Därtill kan datorn modellera en objektiv funktion för att bestämma vilka lån i gruppen av lån som uppfyller ett eller flera hinder är minst lönsamma för värdepapperisering i värdepapperiseringsmodellen och fördela de lån som uppfyller en eller flera begränsningar och är minst lönsamma för värdepapperisering i lånepaketet. En annan aspekt av föreliggande uppfinning åstadkommer en metod för att optimera helränshandel med fast ränta. Denna metod innefattar stegen att välja en befolkning av lån som väljer ett eller flera lån som uppfyller ett budsättning som bestämmer ett pris på varje lån som uppfyller begränsningen baserat på en värdepapperiserad modell som bestämmer om en effektiv modell ska användas för att välja vilken av de Ett eller flera lån är minst gynnsamma att vara värdepapperiserade. Vidare, om den effektiva modellen används, innefattar metoden val av vilket av pone eller fler lån som är minst gynnsamma för att vara värdepapperiserat med minsta dollarvärde av spridningen. En annan aspekt av föreliggande uppfinning åstadkommer ett system för optimalt poolning av överskottskupong som härrör från värdepapperiseringslån. Systemet innehåller och nätverk och en dator som kan överföras till nätverket. Vidare skapar datorn en modell som motsvarar överflödiga kupongobligationspuljer och en odelad pool, varje överskottskupongbindningspool som inkluderar minst en begränsning och behandlar modellen för att fördela var och en av lånen till antingen en överskott av kupongbindningspoolen eller i den odelade poolen för att maximera det totala marknadsvärdet för den överskjutande kupongen som tilldelas de överliggande kupongbindningspoolerna. Dessa och andra aspekter, särdrag och utföringsformer av uppfinningen kommer att bli uppenbara för en person med normal kunskap på området vid beaktande av följande detaljerade beskrivning av illustrerade utföringsformer som exemplifierar det bästa sättet att utföra uppfinningen som för närvarande uppfattas. KORT BESKRIVNING AV RITNINGARNA För en mer fullständig förståelse av de exemplifierande utföringsformerna av föreliggande uppfinning och fördelarna därav hänvisas nu till följande beskrivning tillsammans med de bifogade figurerna som kort beskrivs som följer. FIKON. 1 är ett blockschema som visar ett system för att optimera helränshandeln med fast ränta i enlighet med en exemplifierande utföringsform av föreliggande uppfinning. FIKON. 2 är ett flödesschema som visar ett förfarande för att optimera helränshandeln med fast ränta i enlighet med en exemplifierande utföringsform av föreliggande uppfinning. FIKON. 3 är ett flödesschema som visar en metod för att bestämma en värdepapperiseringsstrategi för en population av lån i enlighet med en exemplifierande utföringsform av föreliggande uppfinning. FIKON. 4 är ett flödesschema som visar ett förfarande för att förpacka en befolkning av lån till en pensionärstruktur enligt en exemplifierande utföringsform av föreliggande uppfinning. FIKON. 5 är ett flödesschema som visar ett förfarande för att förpacka en population av lån till en pensionärstruktur enligt en exemplifierande utföringsform av föreliggande uppfinning. FIKON. 6 är ett flödesschema som visar en metod för att förpacka en population av lån för att passera genom bindningar i enlighet med en exemplifierande utföringsform av föreliggande uppfinning. FIKON. 7 är ett flödesschema som visar en metod för att förpacka hela lån i enlighet med en exemplifierande utföringsform av föreliggande uppfinning. FIKON. 8 är ett flödesschema som visar en metod för att samla överskottskupong i enlighet med en exemplifierande utföringsform av föreliggande uppfinning. Detaljerad beskrivning av exemplifierande utföringsformer Uppfinningen tillhandahåller datorbaserade system och metoder för att optimera helränshandel med fast ränta. Specifikt tillhandahåller uppfinningen datorbaserade system och metoder för att optimalt förpacka en befolkning av hela lån till obligationer i antingen en seniorbaserad obligationsstruktur eller i pooler av passera genom värdepapper garanterade av en statlig myndighet. Modeller för varje typ av obligationsstruktur bearbetas på lånpopulationen tills antingen en optimal bindningspaket hittas eller en användare bestämmer att en lösning med tillräcklig hög kvalitet finns. Dessutom kan modellerna ta hänsyn till bud för hela lån genom att allokera hela lån som uppfyller kravet på anbudet men som är minst gynnsamma för att bli värdepapperiserade. Även om de exemplifierande utföringsformerna av uppfinningen diskuteras när det gäller hela lån (särskilt fasta bostadsräntor) kan aspekter av uppfinningen också tillämpas för handel med andra typer av lån och tillgångar, såsom lån med rörlig ränta och roterande skulder. Uppfinningen kan innefatta ett datorprogram som innefattar de funktioner som beskrivs häri och illustreras i de bifogade flödesdiagrammen. Det bör dock vara uppenbart att det kan finnas många olika sätt att implementera uppfinningen i datorprogrammering, och uppfinningen bör inte tolkas som begränsad till någon uppsättning datorprograminstruktioner. Vidare skulle en skicklig programmerare kunna skriva ett sådant datorprogram för att genomföra en utföringsform av den beskrivna uppfinningen baserat på flödesschema och associerad beskrivning i applikationstexten. Därför anses inte beskrivning av en särskild uppsättning programkodinstruktioner nödvändiga för en adekvat förståelse av hur man gör och använder uppfinningen. Den uppfinningsenliga funktionaliteten hos det ifrågavarande datorprogrammet kommer att förklaras närmare i den följande beskrivningen, läs i samband med figurerna som illustrerar programflödet. Vidare inses det för fackmannen att ett eller flera av de beskrivna stegen kan utföras av hårdvara, mjukvara eller en kombination därav, som kan vara belägna i ett eller flera beräkningssystem. Med hänvisning till ritningarna, i vilka samma siffror representerar liknande element i hela figurerna, kommer aspekter av exemplifierande utföringsformer att beskrivas i detalj. FIKON. 1 är ett blockschema som avbildar ett system 100 för att optimera fullväxelhandel med fast ränta i enlighet med en exemplifierande utföringsform av föreliggande uppfinning. Med hänvisning till fig. 1. Systemet 100 innefattar ett beräkningssystem 110 anslutet till ett distribuerat nätverk 140. Beräkningssystemet 110 kan vara en persondator ansluten till det distribuerade nätverket 140. Beräkningssystemet 110 kan innefatta en eller flera applikationer, såsom lånehandeloptimeringsapplikation 120. Denna exemplifierande lånehandeloptimerare 120 innefattar fyra moduler 121-124 som kan fungera individuellt eller interagera med varandra för att tillhandahålla en optimal förpackning av lån till en eller flera bindningsstrukturer och hela lånepaket. En pensionärmodul 121 distribuerar lån till en äldrepensionsstruktur med obligationer som har olika kreditbetyg och olika nettouppvärden. Såsom kommer att diskuteras mer i detalj med hänvisning till fig. 4-5. Seniorsubordinatmodulen 121 distribuerar lånen till obligationer med AAA-rating, underordnade obligationer med lägre kreditbetyg och beroende på lånen och kupongvärdena för AAA-obligationerna och de underliggande obligationerna, räntebindningarna och de viktigaste obligationerna. En pass-through-modul 122 distribuerar lån för att passera genom obligationer garanterade av en offentlig myndighet, till exempel Freddie Mac eller Fannie Mae. Pass-through-modulen 122 samlar upp lånen optimalt för att bli meddelad (TBA) genom värdepapper baserat på olika begränsningar. Pass-thru-modulen 122 diskuteras mer detaljerat nedan med hänvisning till fig. 6. En hellånsmodul 123 fördelar lån för att möta bud för låneportföljer som uppfyller specifika krav och begränsningar i budet. Hela lånemodulen 123 kan interagera med antingen seniorsubordinatmodulen 121 eller pass-thru-modulen 122 för att allokera lån som uppfyller kraven för buden men är mindre gynnsamma för att vara värdepapperiserad. Hela lånemodulen 123 diskuteras nedan mer i detalj med hänvisning till fig. 7. En överskottskupongmodul 124 distribuerar överskottskuponger av värdepapperiserade lån till olika obligationsräntor eller pooler. Den överskjutande kupongmodulen 124 kan poola överskjutande kuponger som härrör från seniorsubordinatbindningsstruktur skapad av seniorsubordinatmodulen 121 och överflödiga kuponger som härrör från att passera genom värdepapper som skapats av pass-thru-modulen 122. Överskottskupongmodulen 124 diskuteras nedan mer i detalj med hänvisning till fig. 8. Användare kan mata in information till ett användargränssnitt 115 i databehandlingssystemet 110. Denna information kan innefatta en typ av obligationsstruktur för att optimera, begränsningar som hör samman med obligationsstrukturer och obligationspooler, information i samband med lånebud och all annan information som krävs av lånehandelsoptimeraren 120. Efter att informationen har tagits emot av användargränssnittet 115. Informationen lagras i en datalagringsenhet 125. som kan vara en mjukvaru databas eller annan minnesstruktur. Användare kan också välja en befolkning av lån att överväga för optimering genom användargränssnittet 115. Lånen kan lagras i en databas som är lagrad på eller kopplad till beräkningssystemet 110 eller hos en datakälla 150 som är ansluten till det distribuerade nätverket 140. Användargränssnittet 115 kan även till en användare mata ut bindningspaket och hela lånepaket bestämda av lånehandelsoptimeraren 120. Lånhandeloptimeraren 120 kan kommunicera med flera datakällor 150 med hjälp av det distribuerade nätverket 140. Lånhandeloptimeraren 120 kan exempelvis kommunicera med en datakälla 150 för att bestämma Fannie Mae TBA-priser och en annan datakälla 150 för att bestämma amerikanska statsobligationspriser. I ett annat exempel kan lånehandelsoptimeraren 120 kommunicera med en datakälla 150 för att få tillgång till information i samband med bud för hela lånepaket. Det distribuerade nätverket 140 kan vara ett lokalt nätverk (LAN), wide area network (WAN), Internet eller annan typ av nätverk. FIKON. 2 är ett flödesschema som visar ett förfarande 200 för att optimera fullväxelhandel med fast ränta i enlighet med en exemplifierande utföringsform av föreliggande uppfinning. Med hänvisning till fig. 1 och 2. vid steg 205. användargränssnittet 115 mottar inmatning från en användare. Denna användarinmatning används av låneoptimeringsoptimeraren 120 för att fastställa obligationsstrukturen som bör optimeras för en befolkning av lån. Till exempel, om användaren önskar hitta den optimala sammanslagningen av lån för att passera genom obligationer, kan användaren ange begränsningarna för varje obligationspool. Exempel på begränsningar för passera genom obligationspooler inkluderar begränsningar på lånebalanser, totalt antal lån för en pool och total lånebalans för en pool. Vid steg 210. en befolkning av lån väljs ut för optimering. Befolkningen av lån kan väljas från lån som lagras i en lånedatabas lagrad på eller kopplad till beräkningssystemet 110 eller från en databas vid en datakälla 150 ansluten till det distribuerade nätverket 140. Befolkningen av lån kan innefatta lån som för närvarande ägs av användaren (t ex investeringsbank) av låneoptimeringsoptimeraren 120 andor lån som upphandlas av en annan bank, låneinstitut eller annan institution. Till exempel kan en användare använda låneoptimeringsoptimeraren 120 för att hitta det maximala marknadsvärdet för en låneportfölj som för närvarande säljs för att bestämma ett optimalt bud på låneportföljen. Dessutom kan en användare välja befolkningen i lån genom att specificera vissa kriterier, såsom maximal lånebalans, placering av lånen och FICO-poäng. Vid steg 215. Lånhandeloptimeringsenheten 120 fastställer en värdepapperiseringsstrategi för befolkningen i lån som valts i steg 210. Beroende på användarinmatningarna mottagna i steg 205. lånehandelsoptimeraren 120 sysselsätter en eller flera av de seniorsubordinära modulerna 121. pass-thru-modulen 122. och hela lånemodulen 123 för att bestämma värdepapperiseringsstrategin för befolkningen i lån. Steg 215 diskuteras mer i detalj med hänvisning till fig. 3-7. Vid steg 220. låneoptimeringsoptimeraren 120 bestämmer huruvida den värdepapperiseringsstrategi som returneras i steg 215 är av tillräckligt hög kvalitet. I denna exemplifierande utföringsform återger lånehandelsoptimeraren 120 steget att bestämma en värdepapperiseringsstrategi för befolkningen i lån tills antingen en optimal lösning hittas eller användaren bestämmer att värdepapperiseringsstrategin är av tillräckligt hög kvalitet. För att användaren ska kunna bestämma om värdepapperiseringsstrategin, om den har tillräcklig hög kvalitet, kan lånehandelsoptimeraren 120 mata resultaten till användaren genom användargränssnittet 115. Lånhandeloptimeraren 120 kan mata ut dessa resultat baserat på ett antal iterationer från steg 215 (t ex varje 100 iterationer) eller när en viss kvalitetsnivå hittas. Användargränssnittet 115 kan sedan få in ingång från användaren som indikerar huruvida värdepapperiseringsstrategin är av tillräcklig hög kvalitet. Om värdepapperiseringsstrategin är av tillräcklig hög kvalitet eller optimal fortsätter metoden 200 till steg 225. I annat fall återgår metoden 200 till steg 215. I en exemplifierande utföringsform mäts kvaliteten i förhållande till det totala dollarn värdet av befolkningens befolkning. Till exempel kan användaren vilja sälja en befolkning av lån för minst tio miljoner dollar för att kunna bjuda på lånen. Användaren kan ställa in ett tröskelvärde för lånehandelsoptimeraren 120 för att bara returnera en lösning som uppfyller detta tröskelvärde eller en lösning som är den optimala lösningen om den optimala lösningen ligger under denna tröskel. Vid steg 225. överskottskupongmodulen 124 i lånehandelsoptimeraren 120 kan poola eventuell överskjutande kupong som härrör från värdepapperiseringsstrategin bestämd i steg 215. Detta steg är valfritt och diskuteras nedan mer i detalj med hänvisning till fig. 8. Vid steg 230. the loan trading optimizer 120 communicates the final securitization strategy to the user interface 115 for outputting to a user. The user interface 115 can display the final securitization strategy and optionally other possible securitization strategies with similar quality levels. FIG. 3 is a flow chart depicting a method 215 for determining a securitization strategy for a population of loans in accordance with one exemplary embodiment of the present invention. Referring to FIGS. 1 and 3. at step 305 . the loan trading optimizer 120 determines which models to use for determining the securitization strategies. In this exemplary embodiment, the loan trading optimizer 120 includes a seniorsubordinate module 121 . a pass-thru module 122 . and a whole loan module 123 . Each of the modules 121 - 123 can build and process a model for determining an optimal packaging of loans as discussed below. The loan trading optimizer 120 determines which modules 121 - 123 to use based on the input received from the user in step 205 of FIG. 2. For example, the user may specify that only a seniorsubordinate structure should be optimized for the population of loans. Alternatively, if the user has entered bid information for a portfolio of whole loans, the loan trading optimizer 120 can execute the whole loan module 123 with the seniorsubordinate module 121 andor the pass-thru module 122 to determine which of the loans meet the requirements of the bid and are least favorable for securitization. Additionally, a user may specify that both an optimal seniorsubordinate bond structure and an optimal pooling of pass through bonds should be determined for the population of loans. If the user selected that a seniorsubordinate bond structure should be optimized, the method 215 proceeds to step 310 . At step 310 . the seniorsubordinate module 121 develops a model for packaging the population of loans into a seniorsubordinate bond structure and processes the model to determine an optimal seniorsubordinate bond structure for the loan population. Step 310 is discussed in more detail with reference to FIGS. 4 and 5. After the seniorsubordinate structure is determined, the method 215 proceeds to step 220 ( FIG. 2 ). If the user selected that the population of loans should be optimally pooled into pass through bonds, the method 215 proceeds to step 315 . At step 315 . the pass-thru module 122 develops a model for pooling the population of loans into multiple bond pools and processes the model to determine an optimal pooling for the loan population. Step 315 is discussed in more detail with reference to FIG. 6. After the pooling is determined, the method 215 proceeds to step 220 ( FIG. 2 ). If the user selected that whole loans should be allocated to a package of whole loans to be sold, the method 215 proceeds to step 320 . At step 320 . the whole loan module 123 develops a model for allocating whole loans that meet certain constraints and are less favorable to be securitized into a whole loan package and processes the model to determine which loans are best suited for the whole loan package. Step 320 is discussed in more detail with reference to FIG. 7. After the whole loan package is determined, the method 215 proceeds to step 220 ( FIG. 2 ). FIG. 4 is a flow chart depicting a method 310 for packaging a population of loans into a seniorsubordinate bond structure in accordance with one exemplary embodiment of the present invention. As briefly discussed above with reference to FIG. 1. a seniorsubordinate bond structure is a structure where bonds with different credit ratings are created. Typically, the seniorsubordinate bond structure includes a senior tranche of bonds having a AAA or similar credit rating and a subordinate tranche of bonds having a lower credit rating. The senior tranche is protected from a certain level of loss by the subordinate tranche as the subordinate tranche incurs the first losses that may occur. The senior trance can be sold to investors desiring a more conservative investment having a lower yield, while the subordinated tranche can be sold to investors willing to take on more risk for a higher yield. For the purpose of this application, a AAA rated bond refers to a bond in the senior tranche, but not necessarily a bond having a credit rating of AAA. Additionally, interest only (IO) and principal only (PO) bonds may be created in a seniorsubordinate structure. An IO bond is created when the net coupon of a loan is more than the coupon of the bond in which the loan executes. Thus, the difference in the loan coupon and the bond coupon creates an interest only cash flow. Similarly, when the loan coupon is less than the bond coupon, a PO bond is created which receives only principal payments. Referring to FIGS. 1 and 4. at step 405 . the seniorsubordinate module 121 determines the bond coupons that are available for executing the loans into. The seniorsubordinate module 121 may obtain the available bond coupons from a data source 150 or may receive the available bond coupons from the user by way of the user interface 115 in step 205 of FIG. 2. For example, the user may desire to execute the loans into bonds having coupon values between 4.5 and 7.0. At step 410 . the seniorsubordinate module 121 selects a first bond coupon value from the range of available bond coupon values. This first coupon value can be the lowest bond coupon value, the highest coupon value, or any other bond coupon value in the range of available bond coupon values. At step 415 . the seniorsubordinate module 121 determines the execution price of each loan in the population of loans at the selected coupon value. Each loan in the population of loans is structured as a bond. The cash flow of each loan is distributed into symbolic AAA and subordinate bonds, and depending on the coupon of the loan and the selected bond coupon, an IO or PO bond. The principal payment and interest cash flows of each loan is generated in each period accounting for loan characteristics of the loan, such as IO period, balloon terms, and prepayment characteristics. The cash flow generated in each period is distributed to all bonds that the loan executes taking into account shifting interest rules that govern the distribution of prepayments between the AAA and the subordinate bonds in each period. The proportion in which the principal payments are distributed depends on the subordination levels of the AAA and the subordinate bonds. The subordination levels are a function of the loan attributes and are supplied by rating agencies for each loan through an Application Program Interface (API) coupled to the computing device 110 . Prepayments are first distributed pro rata to the PO bond and then between the AAA and the subordinate bonds based on the shifting interest rules. Any remaining prepayment is distributed proportionally among all the subordinate bonds. The interest payment for each of the bonds is a direct function of the coupon value for the bond. After the cash flows of each of the bonds for each of the loans have been generated, the present value of these cash flows is determined. For fixed rate loans, the AAA bonds can be priced as a spread to the To Be Announced (TBA) bond prices. However, the subordinate bond cash flows are discounted by a spread to the U. S. Treasury Yield Curve. The IO and PO bonds are priced using the Trust IO and PO prices. Finally, the price of the AAA bond, the subordinate bonds, and the IO or PO bond is combined proportionally for each loan based on the bond sizes to get the final bond price for each loan. This final bond price is the price of the loan executing into the bond given the selected coupon value of the bond. At step 420 . the seniorsubordinate module 121 determines if there are more bond coupon values in the range of available bond coupon values. If there are more bond coupon values, the method 310 proceeds to step 425 . Otherwise, the method 310 proceeds to step 430 . At step 425 . the next bond coupon value in the range of available bond coupon values is selected. In one exemplary embodiment, the seniorsubordinate module 121 can increment from the previous selected bond coupon value (e. g. 0.5 increments) to determine the next bond coupon value. In an alternative embodiment, the seniorsubordinate module 121 can progress through a fixed list of bond coupon values. For example, the user may select specific bond coupon values to execute the loans into, such as only 4.0, 5.0, and 6.0. After the next bond coupon value is selected, the method 310 returns to step 415 to determine the execution price of each loan in the population of loans at the new coupon value. At step 430 . the seniorsubordinate module 121 determines, for each loan in the population of loans, which bond coupon value yielded the highest final bond price for that particular loan. At step 435 . the seniorsubordinate module 121 groups the loans according to the bond coupon value that yielded the highest final bond price for each loan. For example, if the available bond coupon values are 4.0, 5.0, and 6.0, each loan that has a highest final bond price at 4.0 are grouped together, while each loan that has a highest final bond price at 5.0 are grouped together, and each loan that has a final bond price at 6.0 are grouped together. After step 435 is complete, the method proceeds to step 220 ( FIG. 2 ). In the embodiment of FIG. 4. the subordinate bonds for each loan execute at the same bond coupon value as the corresponding AAA bond. For example, if a first loan of 6.25 best executes into a bond having a coupon value of 6.0, then a AAA bond of 6.0 and a subordinate bond that is priced at U. S. Treasury spreads specified for execution coupon 6.0 is created. If a second loan of 5.375 best executes into a bond having a coupon value of 5.0, then a AAA bond of 5.0 and a subordinate bond that is priced at U. S. Treasury spreads specified for execution coupon 5.0 is created. This creates two AAA bonds and two subordinate bonds at two different coupon values. Typically, when loans are packaged in a seniorsubordinate bond structure, multiple AAA bonds with multiple coupon values are created with a common set of subordinate bonds that back all of the AAA bonds. This set of subordinate bonds is priced at the weighted average (WA) execution coupon of all of the AAA bonds created for the loan package. Pricing the subordinate bonds at the WA execution coupon implies that the spread to the benchmark U. S. Treasury curve, which is a function of the bond rating and the execution coupon of the subordinate bond, has to be chosen appropriately. In order to know the WA execution coupon of all the AAA bonds for the population of loans, the best execution coupon for each loan in the population of loans has to be known. In order to know the best execution coupon of each loan, the loan has to be priced at different bond coupon values and the AAA and subordinate bonds created at those coupons also have to be priced. However, the subordinate bond cash flows are discounted with spreads to the U. S. Treasury, with spreads taken at the WA best execution coupon which is still unknown. This creates a circular dependency as the best execution of each loan in the population of loans now depends on all the other loans in the population. FIG. 5 is a flow chart depicting a method 500 for packaging a population of loans into a seniorsubordinate structure in accordance with one exemplary embodiment of the present invention. The method 500 is an alternative method to that of method 310 of FIG. 4. accounting for pricing subordinate bonds at the WA execution coupon and provides a solution to the circular dependency discussed above. The WA execution coupon for a population of loans can be calculated by: In Equation 1, x ij is a binary variable with a value of either 0 or 1, whereby a value of 1 indicates that the i th loan is optimally executing at the j th execution coupon value. The parameters d 0 to d j represent the j execution coupon values. For example, the coupons values could range from 4.5 to 7.0. Finally, the parameter b i represents the balance of the i th loan. If q o to q j are the weights of the j execution coupons, then: where q 0 to q 1 are special ordered sets of type two, which implies that at most two are non-zero and the two non-zero weights are adjacent. Let Pa ij be the price of the AAA bond when loan i executes at coupon j. Next, let Ps ij be the overall price of all of the subordinate bonds combined when loan i executes at coupon j. Finally, let Pio ij and Ppo ij be the prices of the IO and PO bonds respectively when loan i executes at coupon j. The AAA bond prices and the IO and PO bond price components of loan i executing at coupon j are linear functions of x ij . The AAA priced as a spread to the TBA is a function of the execution coupon of the AAA bond and the IOPO prices are a lookup based on collateral attributes of the loan. However, pricing the subordinate bonds is complicated because the subordinate cash flows are discounted at the WA execution coupon. Let P i be a matrix of size jj that contains the prices of the subordinate bonds. The (m, n) entry of the matrix represents the price of the subordinate cash flows when the cash flow of loan i is generated assuming that loan i executes at the m th coupon and is discounted using subordinate spreads for the n th coupon. Subordinate spreads to the U. S. Treasury are a function of the execution coupon and any product definition, such as the size (e. g. JumboConforming), maturity (e. g. 1530 years), etc. The price of the subordinate bond of the i th loan can be written as: which is a non linear expression as the equation contains a product of q and x ij . both of which are variables in this equation. FIG. 5 provides a method 500 for overcoming this non-linearity. Referring to FIG. 5. at step 505 . the seniorsubordinate module 121 determines the optimal execution price for each loan in the population of loans independent of the WA execution coupon. In one exemplary embodiment, the seniorsubordinate module 121 employs the method 310 of FIG. 4 to find the optimal execution price for each loan. At step 510 . the seniorsubordinate module 121 determines the WA execution coupon corresponding to the optimal execution price for each loan. This WA execution coupon can be found using Equation 1 above. At step 515 . the seniorsubordinate module 121 determines the weights (i. e. q 0 q j ) of each execution coupon for the WA execution coupon found in step 510 . These weights can be found using Equation 3 above. At step 520 . the seniorsubordinate module 121 builds a model including an objective function to determine the optimal execution coupon for each loan to maximize the total market value of all of the bonds in the seniorsubordinate structure. The expression of the objective function contains ij terms, where the ij term represents the market value of executing the i th loan at the j th execution coupon. After inserting the values of the weights of the execution coupons (i. e. qs) into the expression for subordinate bond price (Equation 4), only two of the terms will be non-zero for the sub-price of the i th loan executing at the j th execution coupon. As the method 200 of FIG. 2 iterates step 215 . different WA execution coupons can be used to maximize the objective function. The iterations can begin with the WA execution coupon found in step 510 and the seniorsubordinate module 121 can search around this WA execution coupon until either the optimal solution is found or the user decides that a solution of sufficient high quality is found in step 220 of FIG. 2. In other words, the seniorsubordinate module 121 searches for an optimal solution by guessing several values of the WA execution coupon around an initial estimate of the optimal execution coupon. After a final solution is found by the seniorsubordinate module 121 . the loans can be grouped based on the coupon values for each loan in the final solution to the objective function. In some instances, one of the undesirable effects of the seniorsubordinate bond structure is the creation of IO andor PO bonds, which may not trade as rich as AAA bonds. In some exemplary embodiments, the seniorsubordinate module 121 can ameliorate this issue by considering a loan as two pseudo loans. For example, a loan having a net rate of 6.125 and a balance of 100,000 can be considered equivalent to two loans of balance b1 and b2 and coupons 6 and 6.5 such that the following conditions are satisfied: The first condition conserves the original balance, while the second condition is to set the WA coupon of the two pseudo loans to equal the net rate of the original loan. Solving these equations for b1 and b2, we find that b175,000 and b225,000. These two loans, when executed at 6.0 and 6.5 bond coupons respectively, avoids the creation of either an IO bond or a PO bond. Although in the above example two adjacent half point coupons were used to create the two pseudo loans, two coupons from any of the half point bond coupons that are being used to create the bonds can be used. For example, if only bond coupons from 4.5 to 7.0 are being used to create the bonds, there would be fifteen combinations to consider (6C215). In some cases, the best solution is not to split the loan into two adjacent half point bond coupons. For example, this split may not be optimal if the AAA spreads at the two adjacent half point coupons are far higher than the ones that are not adjacent to the net balance of the loan. The seniorsubordinate module 121 can construct a linear program or linear objective function to determine the optimal split into pseudo loans. The output of the linear program is the optimal splitting of the original loan into pseudo loans such that the overall execution of the loan is maximized, subject to no IO bond or PO bond creation. For each loan i, let variable x ij indicate the balance of loan i allocated to the jth half point coupon, subject to the constraint that the sum of over x ij for all j equals to the balance of loan i and the WA coupon expressed as a function of the x ij s equals to the net coupon of loan i, similar to Equation 6 above. Let the execution coupons be r 0 to r n . Thus, this equation becomes: where b i is the balance of loan i and c i is the net coupon of loan i. The price of loan i executing at coupon j is the sum of the price of the AAA bond and the subordinate bonds. No IO or PO bonds are created when the coupons are split. The seniorsubordinate module 121 calculates the price of the AAA bond as a spread to the TBA, where the spread is a function of the execution coupon j. In one embodiment, the seniorsubordinate module 121 also calculates the price of the subordinate bond as a spread to the TBA for simplification of the problem. Cash flows are not generated as the split of the balances to different execution coupons is not yet known. The seniorsubordinate module 121 combines the price of the subordinate bond and the AAA bond in proportion to the subordination level of loan i, which can be input by a user in step 205 of FIG. 2 or input by an API. At this point, the seniorsubordinate module 121 has calculated the price of loan i (P ij ) for each execution coupon j. To determine the optimal splitting of the original loan into pseudo loans, the seniorsubordinate module 121 creates the following objective function and works to maximize this objective function: Equation 8 is a simple linear program with two constraints and can be solved optimally. The solution gives the optimal split of the loan into at most two coupons and thus, a bond can be structured without creating any IO or PO bonds. The user can determine if the bond should be split or not based on the optimal execution and other business considerations. FIG. 6 is a flow chart depicting a method 315 for packaging a population of loans into pass through bonds in accordance with one exemplary embodiment of the present invention. A pass through bond is a fixed income security backed by a package of loans or other assets. Typically, as briefly discussed above with reference to FIG. 1. a pass through bond is guaranteed by a government agency, such as Freddie Mac or Fannie Mae. The government agency guarantees the pass through bond in exchange for a guarantee fee (Gfee). The Gfee can be an input provided by the agencies for a specific set of loans or can be specified as a set of rules based on collateral characteristics. Regardless of how the Gfee is obtained, the Gfee for a loan set is known. When loans are securitized as a pass through bond, one has the option to buy up or buy down the Gfee in exchange for an equivalent fee to the agencies. Buying up the Gfee reduces the net coupon and thus the price of the bond as well. This upfront buy up fee is exchanged in lieu of the increased Gfee coupon. Similarly, buying down the Gfee reduces the Gfee and increases the net coupon and therefore increases the bond price. An upfront fee is paid to the agencies to compensate for the reduced Gfee. The Fannie Mae and Freddie Mac agencies typically provide buy up and buy down grids each month. Referring to FIG. 1. these grids can be stored in a data source 150 or in the data storage unit 125 for access by the pass-thru module 122 of the loan trading optimizer 120 . If the Gfee is bought up or bought down, an excess coupon is created. The amount of buy up or buy down of Gfee can vary based on collateral attributes of the loan and can also be subject to a minimum and maximum limit. Referring now to FIGS. 1 and 6. at step 605 . the pass-thru module 122 determines the optimal execution of each loan by buy up or buy down of the Gfee. In one exemplary embodiment, the optimal execution of each loan is determined by finding the overall price of the loan for each available buy up and buy down of the Gfee. Typically, a Gfee can be bought up or down in increments of 1100 th of a basis point. The pass-thru module 122 implements a loop for each loan from the minimum to the maximum Gfee buy up with a step size of 1100 th of a basis point. Similarly, the pass-thru module 122 implements a loop for each loan from the minimum to the maximum Gfee buy down with a step size of 1100 th of a basis point. In each iteration, the amount of Gfee buy up or buy down is added to the current net rate of the loan. From this modified net rate of the loan, the TBA coupon is determined as the closest half point coupon lower than or equal to the modified net rate. The excess coupon is equal to the modified net rate of the TBA coupon and the price of the excess coupon is a lookup in the agency grid. The fee for the buy up or buy down is also a lookup in the agency grid. The price of the TBA coupon is a lookup from the TBA price curve. When the Gfee is bought up, the cost is added to the overall price and when the Gfee is bought down, the cost is subtracted from the overall price. The pass-thru module 122 determines the overall price of execution for the loan at each iteration and determines the optimal execution for the loan as the execution coupon of the TBA for which the overall price is maximized. This overall cost is the combination of the price of the TBA coupon, the price of the excess coupon, and the cost of the Gfee (added if buy up, subtracted if buy down). At step 610 . the pass-thru module 122 determines which TBA pools each loan is eligible for. Pooling loans into TBA bonds is a complex process with many constraints on pooling. Furthermore, different pools of loans have pool payups based on collateral characteristics. For example, low loan balance pools could prepay slower and thus may trade richer. Also, loan pools with geographic concentration known to prepay faster may trade cheaper and thus have a negative pool payup. Thus, pooling optimally taking into account both the constraints and the pool payups can lead to profitable execution that may not be captured otherwise. Each of the TBA pools for which a loan can be allocated has a set of pool eligibility rules and a pool payup or paydown. Non-limiting examples of pools can be a low loan balance pool (e. g. loan balances less than 80K), a medium loan balance pool (e. g. loan balance between 80K and 150K), a high loan balance pool (e. g. loan balances above 150K), a prepay penalty loan pool, and an interest only loan pool. For a loan to be allocated to a specific pool by the pass-thru module 122 . the loan has to satisfy both the eligibility rules of the pool and also best execute at the execution coupon for that pool. The pass-thru module 122 applies the eligibility rules of the TBA bond pools to the loans to determine the TBA bond pools for which each loan is eligible. The pass-thru module 122 can utilize pool priorities to arbitrate between multiple pools if a loan is eligible for more than one pool. If a loan is eligible to be pooled into a higher and lower priority pool, the pass-thru module 122 allocates the loan to the higher priority pool. However, if a loan is eligible for multiple pools having the same priority, the pass-thru module 122 can allocate the loan into either of the pools having the same priority. At step 615 . the pass-thru module 122 builds a model for allocating the loans into TBA pools based on the constraints of each TBA bond pool. Let x ij be a binary variable with a value of 1 or 0 which has a value of 1 when loan i is allocated to TBA bond pool j. The total loan balance and loan count constraints of the TBA pools are linear functions of the x ij variables. The objective function for this model is also a linear combination of the market values of each loan. The primary problem in this model is that the given loan population selected in step 210 of FIG. 2 may not be sufficient to allocate all TBA loan pools, as some of the pools may not have loans to satisfy the balance and count constraints or the loans may not be eligible for those pools. In such cases, it is desirable for the pools to have the constraints when applicable. If there are some pools for which there are not enough loans in the population of loans to form a pool, then such pools are not subjected to the specified constraints while the other pools are. However, it is not possible to know a-priori which pools do not have enough loans to satisfy the constraints. Thus, the model employs conditional constraints to allow constraints to be applicable to only those pools which are allocated. The pooling model is modified to allow for some loans to not be allocated to any pool. This non-allocation will ensure that the model is always solvable and is similar to introducing a slack variable in linear programming. Thus, for each loan in the population of loans, there is an additional binary variable representing the unallocated pool into which the loan can be allocated. Those loans allocated to the unallocated pool are given a zero costmarket value, thus encouraging the pass-thru module 122 to allocate as many loans as possible. The next step in building this pooling model is to introduce p binary variables for the p possible TBA pools. A value of 1 indicates that this pool is allocated with loans satisfying the pool constraints and a value of 0 indicates that this pool is not allocated. These variables are used to convert simple linear constraints into conditional constraints. Each constraint of each pool is converted to conditional constraints for the pooling model. To detail this conversion, a maximum loan count constraint is considered for pool P. Let x 1 to x n be binary variable where x i are the loans eligible for pool P. Next, let x 1 . x n U, where U equals the total number of loans in pool P. Finally, let w be the binary variable to indicate if pool P is allocated. The user constraint for maximum loan count is specified as UK, where K is given by the user. In order to impose this constraint conditionally, this constraint is transformed to the following two constraints: UK w UM w where M is a constant such that the sum of all x i s is bounded by M. Consider both the cases when pool P is allocated (w1) and when pool P is not allocated (w0) below: w1: UK (required) UM (redundant) w0: U0 U0 The only way for U0 would be when all the x i s are 0 and thus, pool P will be unallocated. Other constraints, such as minimum count, minimum balance, maximum balance, average balance, and weighted average constraints can be transformed similarly for the pooling model. After all of the constraints are transformed to conditional constraints, the pooling model is ready to handle constraints conditionally. At step 620 . the pass-thru module 122 executes the pooling model to allocate the loans into TBA pools. After the pass-thru module 122 executes the model for one iteration, the method 315 proceeds to step 220 ( FIG. 2 ). As the method 200 of FIG. 2 iterates step 215 . different TBA pool allocations are produced by the pass-thru module 122 until either the optimal TBA pool allocation is found or until the user decides that a solution of sufficient high quality is found in step 220 ( FIG. 2 ). FIG. 7 is a flow chart depicting a method 320 for packaging whole loans in accordance with one exemplary embodiment of the present invention. The method 320 identifies an optimal package of loans meeting a set of constraints given by a customer or investor. In this embodiment, the loan package is optimized by determining which loans, among the population of loans that meet the constraints, are least favorable to be securitized. Although the method 320 of FIG. 7 is discussed in terms of the seniorsubordinate bond structure, other bonds structures or models can be used. Referring to FIG. 7. at step 705 . the whole loan module 123 determines which loans in the population of loans meets constraints of a bid for whole loans. Investment banks and other financial institutions receive bids for whole loans meeting specific requirements. These requirements can be entered into the user interface 115 at step 205 of FIG. 2 andor stored in the data storage unit 125 or a data source 150 . The constraints can include requirements that the loans must satisfy, such as, for example, minimum and maximum balance of the total loan package, constraints on the weighted average coupon, credit ratings of the recipients of the loans (e. g. FICO score), and loan-to-value (LTV) ratio. The constraints can also include location based constraints, such as no more than 10 of the loan population be from Florida and no zip code should have more than 5 of the loan population. After the whole loan module 123 selects the loans that meet the constraints, at step 710 . the whole loan module 123 determines the price of each loan that meets the constraints based on a securitization module. For example, the price of the loans may be calculated based on the seniorsubordinate structure discussed above with reference to FIGS. 4 and 5 . At step 715 . the whole loan module 123 determines whether to use an efficient model to select loans least favorable to be securitized by minimizing the dollar value of the spread of execution of the loans based on a securitization model or a less efficient model to select loans least favorable to be securitized by minimizing the spread of execution of the loans based on a securitization model. In one exemplary embodiment, this determination can be based on the total number of loans in the population or chosen by a user. If the whole loan module 123 determines to use the efficient model, the method 320 proceeds to step 725 . Otherwise, the method 320 proceeds to step 720 . At step 720 . the whole loan module 123 selects loans that are least favorable to be securitized by minimizing the spread of execution of the loans based on the seniorsubordinate bond structure. The whole loan module 123 builds a model to select a subset of the loans that meet the constraints such that the WA price of the loans of this subset net of the TBA price of the WA coupon of this subset is minimized. The TBA price of the WA coupon of the subset is typically higher as the TBA typically has a better credit quality and hence the metric chosen will have a negative value. The objective function that needs to be minimized is given by: In Equation 9, x 1 to x n are binary variables with a value of either 0 or 1, whereby a value of 1 indicates that the loan is allocated and 0 otherwise. The variables b 1 to b n are the balances of the loans and p 1 to p n are the prices of the loans as determined in step 710 . The variables q 1 to q m are the weights for each of the half point coupons and px 1 to px m are the TBA prices for the half point coupons. The weights are special ordered sets of type two, which as discussed above, implies that at most two are non-zero and the two non-zero weights are adjacent. Thus, the expression (q 1 px 1 . q m px m ) is the price of the WA coupon of the allocated loans. The weights (q 1 - q m ) are subject to the constraints: The equations above are analyzed when z i is set to 1 and z i is set to 0 and which shows that y i will be y 0 or zero within a tolerance of eps. Eps is a model specific constant and is suitably small to account for lack of numerical precision in a binary variable. The tolerance eps is utilized in this model as although binary variables are supposed to be 0 or 1, the binary variables suffer from precision issues and thus, the model should accommodate numerical difficulties. The source of this precision issue is the way y 0 has been defined. The denominator of y 0 M(x 1 b 1 . x n b n ) is essentially the sum of the balances of all loans in the pool, which can be a very large number resulting in a small y 0 . After building the model, the whole loan module 123 minimizes the objective function in Equation 13 with each iteration of step 215 of FIG. 2 while maintaining the constraints of the subsequent equations 17- 21 . The loans that are allocated into the whole loan package are the loans that meet the constraints of the bid and have a y value equal to y 0 . After step 720 is completed, the method 320 proceeds to step 220 ( FIG. 2 ). At step 725 . the whole loan module 123 selects loans that are least favorable to be securitized by minimizing the dollar value of the spread of execution of the loans based on the seniorsubordinate bond structure. Thus, the difference of the market value of the allocated loans and the notional market value of the loan pool using the price of the WA execution coupon is minimized. The objective function that needs to be minimized for this model is given by: After building the model, the whole loan module 123 minimizes the objective function in Equation 24 with each iteration of step 215 of FIG. 2 while maintaining the constraints of the subsequent equations 25-29. The loans that are allocated into the whole loan package are the loans that meet the constraints of the bid and have a y value equal to y 0 . After step 725 is completed, the method 320 proceeds to step 220 of FIG. 2. FIG. 8 is a flow chart depicting a method 225 for pooling excess coupon in accordance with one exemplary embodiment of the present invention. The excess coupon module 124 can pool the excess coupon of securitized loans into different tranches or pools. The excess coupon module 124 can take a large population of loans (e. g. 100 thousand or more), each with some excess coupon, and pool the loans into different pools, each pool with a different coupon and specified eligibility rules. Each of the pools can also have a minimum balance constraint. Pools that are created with equal contribution of excess coupon from every loan that is contributing to that pool typically trades richer than pools that have a dispersion in the contribution of excess from different loans. Therefore, it is profitable to create homogeneous pools. Referring to FIG. 8. at step 805 . the excess coupon module 124 converts the pool constraints into conditional constraints as some of the pools defined in this excess coupon model may not have loans to satisfy the pool constraints. This conversion is similar to the conversion of constraints discussed above with reference to FIG. 6. At step 810 . the excess coupon module 124 builds a model to determine the optimal pooling for the excess coupons. Let x ij be the contribution of excess coupon from loan i to pool j. Unlike the pooling model in FIG. 6 above, this variable is not a binary variable. However, an unallocated pool is added to the set of user defined pools which enables the pass-thru module 122 to always solve the model and produce partial allocations. The first constraint of this excess coupon model is the conservation of excess coupon allocated among all the pools for each loan. Any loan that does not get allocated to a user defined pool is placed in the unallocated pool, and thus the unallocated pool is also included in the conservation constraint. In this embodiment, the unallocated pool does not have any other constraint. The objective function of this excess coupon model is to maximize the total market value of the excess that gets allocated. Unallocated excess coupon is assigned a zero market value and thus the solver tries to minimize the unallocated excess coupon. In this model, the excess coupon module 124 tries to create the maximum possible pools with equal excess contribution. Any leftover excess from all the loans can be lumped into a single pool and a WA coupon pool can be created from this pool. An aspect of this excess coupon model is to enforce equality of the excess coupon that gets allocated from a loan to a pool. Furthermore, it is not necessary that all loans allocate excess to a given pool. Thus, the equality of excess is enforced only among loans that have a non-zero contribution of excess to this pool. Let xp 0 to xp p be p real variables that indicate the amount of excess in each pool. Also, let w ij be a binary variable that indicates if loan i is contributing excess to pool. For each eligible loan i, for pool j, the following constraints are added: When M is chosen to be the maximum excess coupon of all loans in the allocation, the expression xp j M is negative. Thus, from x ij 0 and that all excess coupons have to be zero or positive, this implies that x ij 0 when w ij 0. This excess coupon model can be difficult to solve because of its complexity level. In order to reduce the complexity, the excess coupon module 124 employs dimensionality reduction. The first step of this process is to identify the pools into which a loan can be allocated. Eligibility filters in this excess coupon model specify the mapping of the collateral attributes of the loans to the coupons of the pools that the attributes can go into. For example, loans with a net coupon between 4.375 and 5.125 can go into pools of 4.5 or 5.0. Unlike the pooling model discussed above with reference to FIG. 6. there are no pool priorities. At step 815 . the excess coupon module 124 identifies the pool into which a given loan can be allocated based on the collateral attributes of the loan and independent of the pool execution coupon. This gives a one to one mapping between the loans and the pools. At step 820 . the excess coupon module 124 collapses all loans having the same excess coupon within a given pool definition into a single loan. This approach can significantly reduce the number of loans in the loan population. After the population of loans is reduced, the excess coupon module 124 maximizes the objective function at step 825 . The excess coupon module 124 can iteratively determine solutions to the objective function until an optimal solution is found or until a user decides that a solution of sufficient high quality is found. One of ordinary skill in the art would appreciate that the present invention provides computer-based systems and methods for optimizing fixed rate whole loan trading. Specifically, the invention provides computer-based systems and methods for optimally packaging a population of whole loans into bonds in either a seniorsubordinate bond structure or into pools of pass through securities guaranteed by a government agency. Models for each type of bond structure are processed on the population of loans until either an optimal bond package is found or a user determines that a solution of sufficient high quality is found. Additionally, the models can account for bids for whole loans by allocating whole loans that meet requirements of the bid but are least favorable to be securitized. Although specific embodiments of the invention have been described above in detail, the description is merely for purposes of illustration. It should be appreciated, therefore, that many aspects of the invention were described above by way of example only and are not intended as required or essential elements of the invention unless explicitly stated otherwise. Various modifications of, and equivalent steps corresponding to, the disclosed aspects of the exemplary embodiments, in addition to those described above, can be made by a person of ordinary skill in the art, having the benefit of this disclosure, without departing from the spirit and scope of the invention defined in the following claims, the scope of which is to be accorded the broadest interpretation so as to encompass such modifications and equivalent structures. A bank loan trading system and method is provided to utilize an electronic facility to facilitate the trading of bank loans. Sellers and buyers enter offers and bids that are posted to all potential buyers and sellers, unless the orders are undisclosed. It is determined whether there is a match between one of the bids and one of the offers of the same loan. If an order can be filled, the system and method provide various confirmation techniques to ensure that a resultant trade does not violate the terms of the bank loan itself. If an order can be filled partially and the remaining portion of the order may be filled in part or in full, the party entering the initial partial order is given the choice of entering into the second trade. Buyers and sellers also can enter linked orders representing two different orders for the same loan and upon filling one of the linked orders, the other order is canceled. What is claimed is: 1. A bank loan trading method for matching buyers with sellers of bank loans, comprising the steps of: using a computer or other system to post to buyers and sellers bank loan information regarding bank loans for sale entering by one or more of said sellers offers for respective ones of the posted bank loans entering by one or more of said buyers bids or respective ones of the posted bank loans posting to said buyers and sellers the bids and offers for each of the posted bank loans determining whether a match exists between one of said bids and one of said offers for the same bank loan filling the matching bid and offer by conducting a trade between the buyer entering said one of said bids and the seller entering said one of said offers and further comprising the steps of a buyer or a seller or both designating whether a partial order may be filled, for both bids and offers, are carried out by designating an All or None order, a Partial Fill order, or Partial Increm ents Only order said All or None order representing an order having a possible fill amount of only said bank loan dollar amount, said Partial Fill order representing an order having possible fill amounts of increments of a predetermined size greater than the unit of currency of said loan between and including a minimum size and said bank loan dollar amount, and said Partial Increments Only order representing an order having possible fill amounts of said minimum size, incremental amounts greater than said minimum size and less than said bank loan dollar amount in increments of an increment size greater than the unit of currency of said loan, and said bank loan dollar amount, said minimum size and said increment amount being designated by a seller entering said offer or a buyer entering said bid. 2. A bank loan trading method for matching buyers with sellers of bank loans, comprising the steps of: using a computer or other system to post to buyers and sellers bank loan information regarding bank loans for sale entering by one or more of said sellers offers for respective ones of the posted bank loans confirming that filling any possible fill amounts of an entered order would not result in a violation of terms of the respective bank loan being offered entering by one or more of said buyers bids for respective ones of the posted bank loans posting to said buyers and sellers the bids and offers for each of the posted bank loans determining whether a match exists between one of said bids and one of said offers for the same bank loan and filling the matching bid and offer by conducting a trade between the buyer entering said one of said bids and the seller entering said one of said offers wherein the entered offers represent actual offers, and the step of posting the offers for each of the posted bank loans is carried out by rounding each of said actual offers to a nearest interval of a preset dollar amount to provide rounded offers and posting only the founded offers and said step of posting the bids and offers further includes the steps of determining whether each of said rounded offers is within a predetermined offset amount of the respective actual offer and posting information for each of the posted rounded offers indicating whether the respective rounded offer is within the predetermined offset amount of the actual offer. 3. The bank loan trading method of claim 2, wherein said preset dollar amount is 1,000,000, and said predetermined offset amount is 100,000. 4. The bank loan trading method of claim 2, wherein an offer of a subject loan has been posted and further comprising a step of entering by one of said buyers an order exact amount or less or an exact amount or more of said subject loan. 5. A bank loan trading method for matching buyers with sellers of bank loans, comprising the steps of: using a computer or other system to post to buyers and sellers bank loan information regarding bank loans for sale entering by one or more of said sellers offers for respective ones of the posted bank loans confirming that filling any possible fill amounts of an entered order would not result in a violation of terms of the respective bank loan being offered entering by one or more of said buyers bids for respective ones of the posted bank loans posting to said buyers and sellers the bids and offers for each of the posted bank loans determining whether a match exists between one of said bids and one of said offers for the same bank loan filling the matching bid and offer by conducting a trade between the buyer entering said one of said bids and the seller entering said one of said offers wherein the entered offers represent actual offers, and the step of posting the offers for each of the posted bank loans is carried out by rounding each of said actual offers to a nearest interval of a preset dollar amount to provide rounded offers and posting only the rounded offers and the step of entering bids is carried out by entering only bids in intervals of said preset dollar amount and the step of determining whether a match exists is carried out by determining whether a match exists between a bid and the rounded offer for the same bank loan and the step of entering bids or offers further includes the steps of indicating, for each bid or offer, whether a partial order may be filled and entering partial amounts representing portions of said actual bid or actual offer that are acceptable to fill the bid or the offer, with such preset dollar amount being greater than the unit of currency of said loan. 6. A bank loan trading method for matching buyers, with sellers of bank loans, comprising the steps of: using a computer or other system to post to buyers and sellers bank loan information regarding bank loans for sale entering by one or more of said sellers offers for respective ones of the posted bank loans confirming that filling any possible fill amounts of an entered order would not result in a violation of terms of the respective bank loan being offered entering by one or more of said buyers bids for respective ones of the posted bank loans posting to said buyers and sellers the bids and offers for each of the posted bank loans determining whether a match exists between one of said bids and one of said offers for the same bank loan and filling the matching bid and offer by conducting a trade between the buyer entering said one of said bids and the seller entering said one of said offers wherein each of said posted bank loans includes a respective minimum retained amount restricti on that is greater than zero and the step of filling the matching bid and offer is carried out by conducting a trade representing an entire amount or a partial amount of the respective bank loan said bank loan trading process further comprising the steps of determining, when a partial amount of the respective bank loan can be traded, whether an amount of the loan to be retained by the respective seller if the respective loan is partially traded is greater than or equal to the minimum retained amount restriction of the respective loan and preventing the respective seller from entering the respective offer if the respective offer can result in an amount retained by the respective seller that is not greater than or equal to the minimum retained amount restriction of the respective loan. 7. A bank loan trading method for matching buyers with sellers of bank loans comprising the steps of: using a computer or other system to post to buyers and sellers bank loan information regarding bank loans for sale entering by one or more of said sellers offers for respective ones of the posted bank loans entering by one or more of said buyers bids for respective ones of the posted bank loans posting to said buyers and sellers the bids and offers for each of the posted bank loans determining whether a match exists between one of said bids and one of said offers for the same bank loan filling the matching bid and offer by conducting a trade between the buyer entering said one of said bids and the seller entering said one of said offers wherein the step of entering bids further include the step of entering whether the respective bid is disclosed or undisclosed and the step of posting bids and offers posts only the disclosed bids and offers said bank loan trading method further comprisi ng the step of determining whether a match exists between one of said bids and one of said offers for the same bank loan further includes the step of determining, if no match exists for a respective offer and said offer is undisclosed, whether one of said bids for the same bank loan as the undisclosed offer is within a predetermined amount of the undisclosed offer and advising both the respective seller that entered the undisclosed offer and the respective buyer that entered said one of said bids of a proximity of the undisclosed offer and said one of said bids. 8. A system for facilitating trading of bank loans between buyers and sellers comprising: a storage device a processor connected to the storage device, the storage device storing a program for controlling the processor the processor operative with the program to: post to buyers and sellers bank loan information regarding bank loans sale receive from one or more of said sellers offers for respective ones of the posted bank loans receive by one or more of said buyers bids for respective ones of the posted bank loans post to said buyers and sellers the bids and offers for each of the posted bank loans determine whether a match exists between one of said bids and one of said offers for the same bank loan wherein the received indication whether a partial order may be filled, for both bids and offers, designates an All or None order, a Partial Fill order, or a Partial Increments Only order as chosen by a buyer or a seller or both said All or None order representing an order having a possible fill amount of only said bank loan dollar amount, said Partial Fill order representing an order having possible fill amounts of increments of a predetermined size greater than the unit of currency of said loan between and including a minimum size and said bank loan dollar amount, and said Partial Increments Only order representing an order having possible fill amounts of said minimum size, incremental amounts greater than said minimum size and less than said bank loan dollar amount in increments of an increment size, greater than the unit of currency of said loan, and said bank loan dollar amount said processor further receiving said minimum size and said increment amount from a seller supplying an offer or from a buyer supplying a bid. 9. A system, for facilitating trading of bank loans between buyers and sellers comprising: a storage device a processor connected to the storage device the storage device storing a program for controlling the processor the processor operative with the program to: post to buyers and sellers bank loan information regarding bank loans for sale receive from one or more of said sellers offers for respective ones of the posted bank loans confirm that filling any possible fill amounts of an entered order would not result in a violation of terms of the respective bank loan being offered receive by one or more of said buyers bids for respective ones of the posted bank loans post to said buyers and sellers the bids and offers for each of the posted bank loans determine whether a match exists between one of said bids and one of said offers for the same bank loan and notify the buyer entering said one of said bids and the seller entering said one of said offers that their respective bid and offer has been filled wherein the entered offers represent actual offers, and the processor operates to round each of said actual offers to a nearest interval of a preset dollar amount to provide rounded offers and to post only the rounded offers and said processor operates to determine whether each of said rounded offers is within a predetermined offset amount of the respective actual offer and to post to said buyers and sellers information for each of the posted rounded offers indicating whether the respective rounded offer is within the predetermined offset amount of the actual offer. 10. The system of claim 9, wherein said preset dollar amount is 1,000,000, and said predetermined offset amount is 100,000. 11. The system of claim 9, wherein an offer of a subject loan has been posted and said processor receives a bid from one of said buyers in an exact amount or less or an exact amount or more of said subject loan. 12. A system for facilitating trading of bank loans between buyers ad sellers, comprising: a storage device a processor connected to the storage device, the storage device storing a program for controlling the processor the processor operative with the program to: post to buyers and sellers bank loan information regarding bank loans for sale receive from one or more of said sellers offers for respective ones of the posted bank loans confirm that filling any possible fill amounts of an entered order would not result in a violation of terms of the respective bank loan being offered receive by one or more of said buyers bids for respective ones of the posted bank loans post to said buyers and seller the bids and offers for each of the posted bank loans determine whether a match exists between one of said bids and one of said offers for the same bank loan and notify the buyer entering said one of said bids and the seller entering said one of said offers that their respective bid and offer has been filled wherein the entered offers represent actual offers, and the processor operates to round each of said Actual offers to a nearest interval of a preset dollar amount to provide rounded offers and to post only the rounded offers, said processor operates to receive only bids in intervals of said preset dollar amount and to determine whether a match exists between a bid and the rounded offer for the same bank loan and said processor operates to receive an indication from sellers, for each bid or offer, whether a partial order may be filled to receive from the sellers partial amounts representing portions of said actual bid or offer that are acceptable to fill the bid or offer, with such preset dollar amount being greater than the unit of currency of said loan. 13. A system for facilitating trading of bank loans between buyers and sellers comprising: a storage device a processor connected to the storage device the storage, device storing a program for controlling the processor the processor operative with the program to: post to buyers and sellers bank, loan information regarding bank loans for sale receive from one or more of said sellers offers for respective ones of the posted bank loans confirm that filling any possible fill amounts of an entered order would not result in a violation of terms of the respective bank loan being offered receive by one or more of said buyers bids for respective ones of the posted bank loans post to said buyers and sellers the bids and offers for each of the posted bank loans determine whether a match exists between one of said bids and one of said offers for the same bank loan and notify the buyer entering said one of said bids and the seller entering said one of said offers that their respective bid and offe r has been filled wherein each of said posted bank loans includes a respective minimum retained amount restriction that is greater than zero and the processor operates to determine, when a partial amount of the respective bank loan can be traded, whether an amount of the loan to be retained by the respective seller if the respective loan is partially traded is greater than or equal to the minimum retained amount restriction of the respective loan and to cancel the respective offer if the respective offer can result in an amount retained by the respective seller that is not greater than or equal to the minimum retained amount restriction of the respective loan. 14. A bank loan trading method for matching buyers with sellers of ban loans, comprising the steps of: A system for facilitating trading of ban loans between buyers and sellers, comprising: a storage device a processor connected to the storage device, the storage device storing a program for controlling the processor the processor operative with the program to: post to buyers and sellers bank loan information regarding bank loan for sale receive from one or more of said sellers offers for respective ones of the posted bank loans receive by one or more of said buyers bids for respective ones of the posted bank loans post to said buyers and sellers the bids and offers for each of the posted bank loans determine whether a match exists between one of said bids and one of said offers for the same bank loan and wherein said processor operates to receive from buyers indications, for each bid, whether the respective bid is disclosed or undisclosed and to post to buyers and sellers only the dis closed bids and offers and said processor further operates to determine, if no match exists for a respective offer and said offer is undisclosed, whether one of said bids for the same bank loan as the undisclosed offer is within a predetermined amount of the undisclosed offer and to inform both the respective seller that entered the undisclosed offer and the respective buyer that entered said one of said bids of a proximity of the undisclosed offer and said one of said bids. BACKGROUND OF THE INVENTION The present invention relates to a loan trading system and corresponding method and, more particularly, to a loan trading system carried out over the Internet to match buyers and sellers of loans via the matching of bids and offers or through the conducting of auctions. Bank Loan Facilities Large corporations and trusts arrange bank loans in facilities provided by a group of banks and financial institutions, otherwise known as a syndicate. Bank loans typically consist of term loans and revolving credit facilities (also known as revolvers). Term loans are lent to the borrower and have a stated maturity date for repayment. In addition, term loans may be structured with an amortization schedule providing different maturity dates for partial amounts of the term loan with the final payment due on the final maturity date. Term loans may be prepaid but not re-borrowed under the same facility. There may be more than one type or tranche of term loan under the same facility. These term loans are typically differentiated by the maturity date of the tranche. For example, the term loan with the shortest maturity date, typically referred to as the Term Loan A, may require a single amortization or have an amortization schedule with the last payment due on the final maturity date. A longer dated term loan or series of term loans under the same facility may have a maturity date longer than the Term Loan A. For example, a bank loan facility may have a Term Loan A tranche, a Term Loan B tranche with a final maturity date longer than the Term Loan A tranche, and a Term Loan C tranche, with a final maturity date longer than both the Term Loan A and Term Loan B tranches. A revolver provides a commitment from the syndicate for the borrower to draw upon a set amount of money until the maturity date. The commitment is then composed of two portions, the drawn amount and the undrawn amount. The borrower may draw upon the revolver, increasing the drawn amount and reducing the undrawn amount. Part or all of the drawn amount may also be repaid, thereby increasing the availability under the commitment. Draws and repayments may take place continuously until the maturity date when all outstanding amounts are due. There is no requirement that any draw be followed sequentially by a repayment. In some revolving credit facilities, draws may be predicated upon the satisfaction of certain requirements that limit the availability of money to an amount less than the total revolver commitment. These requirements, generally in the form of financial calculations, will generate a maximum available amount that the borrower can draw upon. This restricted amount of funds is typically referred to as the borrowing base. Typically, bank loans have floating interest rates. Borrowed amounts are drawn for intervals which have base interest rates set by industry or bank standards plus an interest rate spread charged to the borrower. For example, funds may be drawn for a number of days, weeks or months. The most common form of base interest rate is the London Interbank Offered Rate or LIBOR. For example, a borrower would inform the bank group of its desire to borrow funds under 1 month LIBOR. The interest rate would then be set for the 1 month interval at the then current 1 month LIBOR interest rate plus the interest rate spread that is set under the facility. At the end of the 1 month period, the money may be repaid or reborrowed for another period, whether or not the period would be the same or different length. In this way, the interest rate is said to float as it is resets periodically. There are generally two types of lenders in bank loan facilities. Banks typically provide loans under the revolver and term loan A tranches. Institutional investors such as mutual funds, privately-raised funds, investment companies or insurance companies typically provide loans under the term loans with longer maturity dates than the term loan A tranche. These term loans, such as the term loan B and the term loan C in the previous example, are typically referred to as institutional term loans. The combination of the term loan A and revolver tranches are typically referred to as the pro rata tranches. To date, the institutional term loans typically have a higher interest rate spread than the pro rata tranches. Other than the differences in the maturity dates and amortization schedules, the lenders under the different tranches typically have the same legal rights under the bank loan facility. Bank Loan Trading An active market has developed for the trading of bank loans. As a private instrument, the trading of bank loans is not subject to the laws pertaining to the trading of public securities. Bank loan trades are conducted by the assignment of the bank loan from one lender to another. Bank loan trades may be arranged through the negotiation of individual parties, with the assistance of brokers, or through an auction. There is no regulation on how these trades are conducted, but assignments typically require the approval of the administrative agent and the borrower. An administrative agent provides the processing of paperwork and movement of funds associated with a bank loan on behalf of the syndicate and the borrower. The approvals typically require that they not be unreasonably withheld. There are generally two restrictions on the assignment of bank loans, compliance with a minimum assignment amount and a minimum retained amount. The minimum assignment amount sets a floor for the amount to be traded and the minimum retained amount pertains to the amount the assignor or seller of the bank loan will continue to hold after assignment of a partial amount of their commitment. The seller may assign its total commitment, but it may not retain a commitment below the minimum retained amount. The participants in the bank loan market include the aforementioned banks and institutions, as well as dealers who make markets in or act as brokers for bank loans. Therefore, there are two types of trades in bank loans: principal and brokered. Principal trades pertain to transactions where a dealer will buy the loan with its own capital and hold the position in inventory until resale. Brokered trades are those that the dealer has arranged for both the purchase of the bank loan from a seller and sale of the bank loan to a buyer. Therefore, the dealer does not risk its own capital on the two transactions. Each trade or assignment generally requires the payment of an assignment fee to the administrative agent of a bank loan facility. Typically, the parties split these fees. In the case of a brokered trade, the dealer will typically pay half the fee for the purchase from the seller and half the fee for the sale to the buyer. Note that a dealer is not required to conduct a trade in such a manner to avoid the buyer and seller learning each others identity. Therefore, a buyer and seller may conduct a single trade to effect the assignment and split the fee amongst themselves. How the Market Functions The loan trading market is considered an over-the-counter market. This means that there is no exchange through which bids and offers are quoted and matched bids and offers are processed. For purposes of this discussion, trading is broken down into two types: trades through interdealer brokers and all other trades. Interdealer brokers match trades between dealers only. The interdealer brokers will market bids and offers, also known as offerings, to the dealers without disclosing the name of the potential buyers and sellers until a bid and offer is matched. The interdealer brokers will market the offerings to dealers either through telephone contact or through the posting of offerings on terminals connected via a direct telephone line to the interdealer brokers computer system. The interdealer broker systems do not use the Internet for transmission. These interdealer broker systems provide limited information that includes only the name of the borrower, the tranche offered or bid, the amount of the bids and offers and the price at which the bids and offers are quoted. To complete a trade, a dealer must contact the interdealer broker by telephone. Trades cannot be completed on the system itself. All other trades consist of those between any of the dealers, bank or institutions. These trades are all conducted by the telephone. Current Electronic Trading Systems The most common form of on-line trading is stock or equity trading. This trading pertains only to publicly-traded securities which are securities that are registered with the U. S. Securities and Exchange Commission. At least a dozen firms have on-line trading websites. All of these websites essentially perform the same function as each other. Clients are able to enter orders into the system connected through the Internet for the purchase or sale of stock that may subsequently be executed through a stock exchange or over the counter market makers. The parameters of the orders are limited to the particular issue of publicly-traded stock, the number of shares to be sold, whether the order requires execution to take place for the entire number of shares indicated (referred to as all or none) or execution is allowable for some part thereof, whether the order will remain open until the end of the day or until canceled (referred to as good for the day and good until canceled, respectively), and order types such as market order (the trade is executed at the currently available bids or offers), limit order (the trade will not occur unless the user receives a bid at or above his required price or an offer at or below his required price), stop order (the trade will occur at the then market price once the security has traded at the price chosen by the user, referred to as the stop price), and stop limit (a limit order that becomes effective once a trade occurs at the stop price). The only differentiation between website-based stock brokerage sites lies in the amount of information to which the users have access. For example, some websites may provide current news and financial statistics, others may include historical data and others may provide analyst research reports. There currently are approximately thirty (30) electronic trading systems engaged in the on-line sale andor trading of one, two or all of treasury, municipal and corporate bonds. These systems can be broken down into dealer systems that allow users to trade only with dealers, but not with each other, cross-matching systems that allow users to trade with each other anonymously, primary market bidding systems that allow users to bid directly on new issues, and a direct issuance system that allows investors to buy securities directly from the issuer. Limited information is available on most of these systems as access is limited to authorized users. There are also financial information websites and direct wireline systems that provide databases of news and financial information to allow for the analysis of issuers of stocks, bonds and derivative securities and their underlying securities. Bloomberg provides one such news and financial information database system and provides to the user the ability to input current information to determine the yield of a bank loan (the rate of return including adjustments for purchase prices with a premium or discount to par measured in terms of two interest rate components, one being the floating rate of interest utilized as a base rate such as LIBOR and the other a numerical measure of the rate of interest). Bloomberg does not provide information on bank loan interest rate spreads after a transaction has closed, nor does it provide a comparative table of bank loan yields. In addition to the above-mentioned limitations and shortcomings of currently available electronic trading systems, currently available financial websites are limited to the trading of financial assets such as even lots of stocks and bonds in the secondary market or the auction of financial assets in the primary market, in other words at the time of their initial issuance, such as the sale of treasury bonds or initial public offering of stock by on-line investment banks. Auction websites of non-financial assets typically are conducted with a non-blind process and a preset end time. Therefore the then highest offer is revealed to users throughout the process and the website typically receives a large influx of bids just prior to the deadline since doing so generally increases the bidders chances of success, whereas earlier bidders efforts go unsuccessful. Bank loan auctions are currently conducted manually by sponsors with the assistance of facsimile and telephone transmission. These manual auctions are limited in the number of participants that may be reached and the process of conducting such manual auctions may not proceed equitably. For example, blind auctions, where bids are not revealed, often do not close at or near their deadlines, indicating that the auctions sponsor is disclosing the highest bid to a favored third party in the hope of an even higher bid. In a further example, sponsors have pulled auctions when bids are too low, thereby wasting the efforts of participants who may do a significant amount of work prior to submitting a bid or offer. OBJECTS OF THE INVENTION It is therefore an object of this invention to provide a bank loan trading system that provides to prospective buyers and sellers information regarding bank loans not previously available to such parties. Another object of the present invention is to provide an electronic matching of buyers and sellers for the trading of bank loans. A further object of the present invention is to provide such electronic matching of buyers and sellers that avoids the shortcoming and limitations of electronic trading systems previously mentioned. An additional object of the present invention is to conduct electronic auctions for bank loans in a fair and equitable manner. These and other objects, advantages and features of the present invention will become readily apparent to those of ordinary skill in the art, and the novel features will be particularly pointed out in the appended claims. SUMMARY OF THE INVENTION In accordance with one embodiment of the present invention, apparatus and method are provided for facilitating the trading of bank loans between buyers and sellers. Bank loan information (e. g. borrower and tranche) regarding bank loans for trading are posted to potential buyers and sellers, sellers and buyers enter offers and bids, respectively, for posted loans and the offers and bids are then posted to all potential buyers and sellers. It is determined whether a match between one of the bids and one of the offers for the same bank loan exists, and if a match exists, the matching bid and offer are filled by conducting a trade between the buyer who entered the bid and the seller who entered the offer. As one aspect of the present invention, only unfilled bids and orders are posted. As a further aspect of the present invention, the seller of a bank loan provides the information regarding a bank loan for sale not previously posted. As an additional aspect of the present invention, when either a bid or an offer is entered by a buyer or seller, respectively, a dollar amount and price of the bid or offer for that bank loan are provided. The type of bid or offer also is provided and identifies the order as an All or None order, a Partial Fill order, or a Partial Increments Only order. The All or None order represents an order having a possible fill amount of only the bank loan dollar amount, the Partial Fill order represents an order having possible fill amounts between and including a minimum partial fill size and the order dollar amount, and the Partial Increments Only order represents an order having possible fill amounts of the minimum size, incremental amounts greater than the minimum size and less than the bank loan dollar amount in increments of an increment size, and the order dollar amount. As a feature of this aspect, a match exists when bids and offers for the same loan with the same price have a common possible fill amount. As yet a further aspect of the present invention, the actual offer is rounded off to the nearest even incremental dollar amount (e. g. 1,000,000) before it is posted and further information is posted that indicates whether the rounded amount is within a predetermined amount (e. g. 100,000) of the actual offer. As yet another aspect of the present invention, a buyer can identify the maximum dollar amount of a loan that can be purchased with respect to a particular posted loan and a trade occurs if the loan is less than or equal to that maximum dollar amount, but if no trade occurs, the buyer is not informed of the actual amount of the offer. As yet an additional aspect of the present invention, offers are rounded to the nearest million dollars prior to determining whether an offer and a bid match. Upon finding a match, it is determined if the amount to be sold is the actual offer amount, which may be an odd amount, or a rounded even dollar amount. Still yet a further aspect of the present invention, offers are accepted only if filling them do not violate the terms (i. e. minimum retained amount and minimum assignment amount) of the bank loan. Still yet another aspect of the present invention, a seller or buyer can enter a linked offer comprised of two orders with a different set of terms for the same bank loan, and upon filling one of these orders, the other order is automatically canceled. Still yet an additional aspect of the present invention, after an order is partially filled in compliance with the orders terms, it is determined whether a second match exists for the unfilled portion of the order. As a further aspect of the present invention, undisclosed bids and offers may be entered which are not posted to buyers and sellers. As a feature of this aspect, if no match is found for an undisclosed order, then it is determined if the undisclosed offer or undisclosed bid is within a predetermined amount of a corresponding bid or offer, and if so, the parties making the respective offer and bid are contacted to see if a match can be made. In accordance with another embodiment of the present invention, apparatus and method are provided for carrying out an auction by placing by a seller of an existing bank loan, disclosing to participants in the bank loan auction information regarding the bank loan for sale, setting by the seller start and end time parameters by designating a start time and an end time, respectively, of the bank loan auction, receiving, after the start time, bids for the bank loan for sale from the participants in the bank loan auction, closing the bank loan auction at the end time, identifying the largest participant who made the largest, and conducting a trade for the bank loan for sale between the seller and said one of the participants. As an aspect of this embodiment, the end time parameter corresponds to an elapsed time interval amount necessary to elapse with no highest bids for the bank loan auction to close. As another aspect of this embodiment, the auction is identified as a blind auction or as a non-blind auction, and the highest bid is posted only during the non-blind auction. As a further aspect of this embodiment, each bid received is comprised of a price and a dollar amount, the bids are ranked by their respective price, a list is generated that includes all necessary ranked bids, starting from the highest ranking and continuing down the ranking, with corresponding dollar amounts that collectively cover the dollar amount of the bank loan, and the participants whose respective bids are included in the list are identified as the buyers. As an additional aspect of this embodiment, the seller sets a minimum acceptable bid, and the trade is discretionary to the seller if the highest bid is less than the minimum acceptable bid. In accordance with a further embodiment of the present invention, apparatus and method are provided for carrying out a reverse-offer bank loan auction by placing by a buyer a bid for a bank loan to be purchased, setting by the buyer start and end time parameters designating a start time and an end time, respectively, of the reverse-offer bank loan auction, receiving, after the start time, offers to sell bank loans from participants in the reverse-offer bank loan auction, closing the reverse-offer bank loan auction at the end time, identifying one of the participants who made the lowest offer, and conducting a trade for the bank loan offered for sale between the one of the participants and the buyer. BRIEF DESCRIPTION OF THE DRAWINGS The following detailed description, given by way of example and not intended to limit the present invention solely thereto, will be best appreciated in conjunction with the accompanying drawings, wherein like reference numerals denote like elements and parts in which: FIG. 1 is a flow chart broadly illustrating the operation of the bank loan trading system of the present invention FIG. 2 is an exemplary webpage that is displayed to users showing quote information FIG. 3 is an exemplary webpage that is displayed to the user when a bid or offer is initiated FIGS. 4A-4D represent a flow chart detailing the specific steps and inquiries taken during the offer and bid input process FIG. 5 is an exemplary order confirmation webpage displayed to a user upon entry of an order FIGS. 6A-6G represent a flow chart detailing the specific steps and inquiries taken during confirming the order and matching of bids and offers in accordance with the present invention FIG. 7 is an exemplary webpage displayed to a user who seeks to schedule an auction FIG. 8 is an exemplary webpage displayed to a user who seeks to make a bid or offer in an auction FIG. 9 is an exemplary webpage displayed to a user participating or sponsoring an auction that requires the user to certify that it complies with particular restrictions of the loans credit agreement and FIG. 10 is an exemplary analytics webpage that can be displayed to a user. DETAILED DESCRIPTION OF CERTAIN PREFERRED EMBODIMENTS The bank loan trading system and corresponding method of the present invention, as hereinafter described, preferably is embodied within an Internet website at a particular website address such as lexc, but other addresses may be used. Users of the present invention, generally buyers (i. e. potential assignees) and sellers (i. e. potential assignors) of bank loans, access the lexc website, enter pertinent and required information as set forth by the lexc website and the lexc website matches buyers with sellers, all as discussed in detail below. It is appreciated that the present invention is not limited to the Internet and may be applied to other public or non-public forums including, but not limited to, intranets. The bank loan trading system of the present invention provides two methods for buyers and sellers to trade bank loans and also presents information with sorting capabilities for the analysis of the bank loan offerings. In the first method for matching buyers and sellers, bids and offers are posted on the lexc website embodying the present invention. The second method entails an electronic auction. Matching of Bids and Offers In accordance with the present invention, the matching of bids and offers is carried out by the process schematically illustrated by the flow chart shown in FIG. 1. Each process and step shown in FIG. 1 is discussed hereinafter. Initially, existing bank loans for sale are displayed to users accessing the website previously mentioned, as represented by step 101 shown in FIG. 1. FIG. 2 is an exemplary webpage that is displayed to users and for convenience herein is identified as the quote page. Of course, existing bank loans and associated information may be displayed to users in various formats. As shown in the quote page shown in FIG. 2. existing bank loans are shown in table 20 . with each loan posted on a separate row of the table. For example, row 20 a displays a loan to the company Allied Waste, row 20 b displays a second loan to Allied Waste and row 20 c displays a loan to the company American Axle. Generally, each loan (i. e. each row of information within table 20 ) includes information pertinent to the loan itself including the loans borrower in column 22 . the tranche in column 24 . the loans base rate in column 26 . the loans base rate spread in column 28 . the interest rate as of date (IRD) in column 30 . whether the IRU is from pre-closing, the inception date or the current date in column 32 . the revolver unutilized commitment fee in column 34 . the maturity date in column 36 and the minimum assignment in column 38 . If applicable, the amount of the loans previous trade is displayed in column 39 (e. g. see FIG. 10 ). Other information pertinent to the loan including, but not limited to, the minimum retained amount, whether the loan interest rate is fixed or based upon a grid, the minimum retained amount, LTM or LQA, quarter ending, debtEBITDA, EBITDAinterest, Moodys long-term rating, Moodys rating security, SPs long-term rating, SPs long-term rating security, and industry also may be displayed. Some of this information may change for each tranche. The bank loan system of the present invention (hereinafter, the system) obtains the above-identified loan information from various known sources. In accordance with the present invention, the system is capable of obtaining information about loans for sale from the users themselves, as represented by block 102 in FIG. 1. Users may enter borrowers and tranches of loans that are not already listed or posted by the system and may enter not-yet listed tranches of loans for sale having borrowers who already are listed by the system. Here, a user provides to the system the borrowers name and the tranche, and the system, either automatically or via supporting personnel, obtains the maturity date and industry of the loan. Other information regarding the loan, mentioned above, may be obtained from the user or through other means. The user-supplied information will be verified by the system andor the supporting personnel prior to the loans posting. In addition to the above-mentioned loan information, table 20 shown in FIG. 2 also displays, if any exist, current bids and offers for each loan. If a bid currently exists for a particular loan, then the bid, the size of that bid, the terms of that bid and the minimum fill size are displayed in the appropriate row in columns 40 . 42 . 44 and 48 . respektive. Similarly, if an offer currently exists for a respective posted loan, then the offer, the size of that offer, so-called odd size information, the terms of that offer and the minimum fill size are shown in columns 50 . 52 . 54 . 56 and 58 . respektive. Information regarding bids and offers shown in columns 40 . 42 . 44 . 46 . 48 . 50 . 52 . 54 . 56 and 58 are discussed further below. The quote page shown in FIG. 2 further includes a table 60 that displays to the user information pertinent to the bids and offers made by that particular user. Other information also is displayed within the quote page, as further discussed below. Bids and Offers Users can enter a bid or offer pertaining to a particular tranche on the listed bank loans, as represented by block 103 in FIG. 1. Such a bid or offer is initiated by selecting an appropriate selection within the quote page shown in FIG. 2. such. as box 70 shown, or by double-clicking a particular row within table 20 . or carrying out another appropriate event. FIG. 3 is an exemplary webpage that is displayed to the user when a bid or offer is initiated. As shown in FIG. 3. the user is asked to enter information about the loan. For example, if the minimum assignment amount is not already in the system, the user will be asked to enter the amount. If the loan has a grid for the base rate spread depending on the financial characteristics of the borrower, then the user will be asked to input the most recent base rate spread and the underlying base rate, as well as supply to the system (e. g. via a facsimile communication) a funding report that verifies the entered information. If the tranche offered is a revolver or pro rata offering of revolver and term loan, then the user will be asked to provide the unutilized commitment fee. In addition to the above user-supplied information, the user is asked to identify how long the order (i. e. bid or offer) will be outstanding. For example, possible choices for expiration include good until cancel, good until the end of the day or good until an expiration date, hour and minute chosen by the user. In addition, orders can be canceled at any time prior to the chosen expiration timedate. Further, the user is asked to enter the bid or offer price and the amount. As is well known, bank debt prices are measured in terms of points which equal the percentage of the par amount of the loan. For example, a price of 99.5 means the loan is priced at 99.5 of the par amount. 99.5 is also 0.5 points less than par. The price tendered and the loan amount equate to that displayed in columns 40 and 42 (for bids) and columns 50 and 52 (for offers) in table 20 in FIG. 2. The user also is asked to enter the terms of the bid or offer with regard to the size of the bank loan willing to be purchased or sold. The terms selected equates to that information displayed in column 44 (for bids) and column 56 (for offers) in table 20 . If the user seeks no partial order, then All or None is selected thereby requiring another users matching bid or offer to match exactly or to closely match (as discussed below with regard to odd) the amount of the current users order. An example of an All or None bid is shown in row 20 c in table 20 of FIG. 2. wherein the bidder (i. e. prospective purchaser) seeks to purchase the entire 5 million of a pro rata loan to American Axle. If the user is willing to enter into a trade of less than the entire amount of the users own bid or offer, then the user can select one of the following two alternative set of terms. The user can select the term Partial FillMinimum Size (Partial Fill) thereby allowing for a matching bid or offer to equal the designated minimum size (which is an even million dollar amount), to equal any even million dollar amount higher than the minimum size and at least one million less than the order amount rounded to the nearest million, or to equal the exact offered amount. As an example of this selection, a user offers 12 million with the requirement Partial Fill5 million and thus the user is willing to enter into a trade in the amounts of 5 million, 6 million, 7 million upwards to 12 million (the entire amount). The user also can select the term Partial IncrementsMinimum Size (Partial Increments Only) as shown in FIG. 3. thereby allowing for a matching bid or offer to equal the designated minimum size, to equal any amount above the minimum in increments of 5 million or some multiple thereof (e. g. 5 million, 10 million, 15 million, etc.) as chosen by the user, or to equal the exact offer amount. As an example of this selection, a user offers 22 million with the requirement Partial 5 Million Increments Only7 Million and thus the user is willing to enter into a trade in the amounts of 7 million (the minimum), 10 million, 15 million, 20 million (representing the partial incremental amounts) or 22 million (the ad entire amount). In another embodiment, the system trades in the amounts of, for example, 7 million (the minimum), 12 million, 17 million, (representing the partial incremental amounts) or 22 million (the entire amount). Thus, the present invention is not limited to the numbers and increments provided herein. Transactions in Odd Amounts Bank loans, unlike bonds, may be held in odd amounts. For example, bonds are typically issued in even 1,000 par amounts. In contrast, bank loans may be allocated amongst a bank group with odd amounts rounded to the nearest cent. In addition, even if the bank loan was allocated in even million dollar increments during syndication, prepayments and scheduled amortization payments may result in borrowers owing odd amounts to members of the bank group. As buyers and sellers may wish to maintain their anonymity, as do the system operators wish to maintain the anonymity of its users prior to the matching of bids and offers (discussed below), and revealing an exact amount offered for sale may provide information that will help identify the seller making an offer, the system displays even million dollar amounts and employs methods, rules and algorithms to provide for trades in odd amounts. The first rule is that buyers must bid in even million dollar amounts. Sellers can make offers in odd amounts, meaning an exact amount to the nearest cent, but that amount will be displayed by the system rounded to the nearest million dollars. In addition to displaying offers rounded off to the nearest million dollars (in column 52 in FIG. 2 ), the system displays the previously mentioned odd size information (in column 54 ) that identifies whether the displayed amount (i. e. the rounded amount) is within 100,000 of the exact amount of the offer. If so, the odd size information column is left blank. If not, the odd size information column is provided with the term odd. For example, an odd 5 million dollar offer represents an offer that falls between the values 4,500,000.01 and 4,899,999.99 or falls between the values 5,100,000.01 and 5,500,000.00. An even 5 million dollar offer therefore represents an exact offer of an amount within (and including) the range 4,900,000.00 and 5,100,000.00. Although it is preferred to utilize an offset of 100,000 as the gauge to identify an offer as odd or even, other amounts, such as 50,000, 75,000, 150,000, etc. may be used. In general, since buyers are highly likely to accept non-exact offers, notification to the potential buyer that an offer either is or is not within 100,000 of the stated amount is, for most purposes, sufficient. If a buyer requires further information, that buyer may inquire further by either personally contacting (e. g. via telephone) personnel operating the system or, alternatively, making an appropriate request via his or her own computer terminal. In either case, however, the system (or its personnel) does not disclose the exact offer amount until after the order has been filled (i. e. the buyer finally accepts). For example, if the buyer can not buy more than 5,250,000 of a loan and the offer is an odd 5 million, the buyer can inform the system (or its personnel) of the 5,250,000 limitation. This action operates as an offer to buy the odd 5 million loan if the exact amount is equal to or below 5,250,000. If the exact offer amount is less than or equal to 5,250,000, then the order is filled, at which time the buyer is informed of the exact amount. On the other hand, if the exact offer amount is greater than 5,250,000, the buyer is advised only that the order was not filled. By obligating the buyer to the above process, buyers are prevented from fishing for information to identify who the seller may potentially be. FIGS. 4A-4D represents a flow chart detailing the specific steps and inquiries taken during the above-discussed order and bid input process. As shown in FIG. 4A. inquiry 200 determines if a bid or offer is being made. For an offer, the process for determining the particular selections to be included within the bid and offer input webpage ( FIG. 3 ) begins at step 201 . Inquiries 202 . 203 and 205 and steps 204 and 206 concern grid, base rate spread, pro rata and revolver information. The minimum assignment amount of the bank loan in issue is either known or entered at inquiry 207 and steps 208 . 209 . The seller then enters the offer at step 210 (FIG. 4 B). If a bid is being made, the buyer enters the bid at step 211 . After the bid or offer is entered, inquiries pertaining to the type of bid or offer are made at steps 212 - 216 . At inquiry 217 (FIG. 4 C), the system inquires as to whether the order is linked (discussed below) and if so, inquiries regarding the linked order are made at steps 218 - 223 . Finally, the user enters the expiration date and time of the offer at inquiry 224 (FIG. 4 D), this information is displayed at step 225 . and a confirmation page (shown in FIG. 5 ) is generated during process 226 (discussed below). Matching of Offers and Bids After at least one bid (by a potential buyer) and at least one offer (by a potential seller) pertaining to the same loan (i. e. the same borrower and tranche) have been entered into the system at the same price or at a price in which the bid exceeds that of the offer, the system carries out the process of determining whether a match exists, as represented by block 104 in FIG. 1. Initially, each offer is rounded to the nearest million dollars and, as required, each bid already is in an even million dollar amount. As previously discussed, each offer and bid can be an All or None type bid, a Partial Fill type bid, or an Partial Increments Only type bid. Offers and bids are compared to one another to determine whether a match exists there between. Using standard logic routines, the existence of matches between offers and bid is obtained. Table 1 below shows example bids and offers, showing both the actual offers and the offers rounded off to the nearest million dollars (in millions), the bids (in millions), as well as the amounts (in millions) of the matches that exist. Prioritizing Multiples Bids and Orders Generally, a better bid for a particular loan is represented by a second bid of the same dollar amount as the first bid but the second bid has a higher price than the first bid. Similarly, a better offer is represented by a second offer of the same dollar amount as the first offer but the second offer has a lower price than the first offer. In these instances, the order with the lower bid or greater offer is canceled and a new order is filled. The following priority is followed when more than one existing order matches a newly entered order: (1) best price (if a bid price exceeds an offer price, the difference between the two is split) (2) largest size (the order that allows the largest amount of the order to be filled is utilized) (3) time priority (if two existing orders match the new order and both provide the same size trade, the first order to be entered is utilized). Compliance with Minimum Assignment and Retained Amount Terms As previously discussed, the seller of a bank loan generally is imposed with two restrictions when assigning the bank loan to a buyer: compliance with the loans minimum assignment amount and the loans minimum retained amount. The minimum assignment amount sets a floor for the amount to be traded and the minimum retained amount pertains to the amount the assignor or seller of the bank loan will continue to hold after assignment of a partial amount of its commitment. These amounts may and often differ from the minimum fill size chosen by users in Partial Fill and Partial Increments Only order fill instructions previously discussed. The loans minimum assignment, if known, is posted in column 38 of table 20 shown in FIG. 2. as previously mentioned. The loans minimum retained amount may be posted in the system, but is currently not embodied in the system. Since bank loans typically provide for both minimum assignment amount and minimum retained amount restrictions, sellers of such loans may have difficulty or be inhibited from using Partial Fill or Partial Increments Only order fill instructions since a partial fill (i. e. an assignment of a portion, not the entire amount, of the loan) may result in the seller retaining less than the minimum retained amount. For example, a seller owns a 17 million loan with a minimum retained amount restriction of 5 million, and the seller seeks to sell as much of the bank loan as possible. Given this scenario, the seller offers the entire loan as a 17 million Partial5 million offer. However, a buyers purchase of 15 million results in the seller retaining 2 million in violation of the bank loan credit agreement. To solve the aforementioned loan violation from occurring, the system of the present invention allows users to create so-called linked orders. A user (a buyer or seller) may enter two bids or two offers with respect to the same loan, and then link those bids or offers so that when one of those bids or offers is filled, the other is immediately canceled. Given the above example wherein the seller owns a 17 million bank loan with a minimum retained amount restriction of 5 million, the seller can enter a 12 million Partial5 million offer (as the first order) and then enter a second linked order as a 17 million All or None offer. If the second order is filled, then the first order is canceled. Conversely, if the first order is filled, the second order is canceled. Table 3 below illustrates the possible outcomes for this example. Since the system seeks to fill the largest orders first, the All or None offer is first attempted to be filled prior to filling partial orders. Additional Trade on Retained Amount If less then the entire amount of an order (bid or offer) is filled, then the system checks whether the amount of the loan retained by the seller or the amount of a bid still unfilled can be filled, as represented by block 106 in FIG. 1. That is, if an offer is partially filled (by the first match), then the system determines whether the unfilled amount (i. e. the amount retained by the seller) can be filled by another bid (a second match). Similarly, if a bid is partially filled (with the first match), then the system determines whether the unfilled amount (i. e. the difference between the bid and the first match) can be filled by another offer (a second match). The above determination of whether a second match is possible (and, if possible, a third match, a fourth match, etc.) is carried out for both linked and non-linked orders. During this determination process, the system repeats the above-discussed matching process for the unfilled amounts and assumes a Partial Fill order fill instruction. This assumption maximizes the chance of a second match. Alternatively, although not preferred, the type of order for unfilled amounts for both offers and bids use the same type of order as the original order (i. e. Partial Fill or Partial Increments Only). If second and subsequent matches are found, the user(s) involved are notified that their offers or bids that are not fully satisfied (i. e. the entire amounts thereof are not bought or sold) can be filled fully or partially by one or more additional trades, depending on the circumstances. Since users generally are obligated to conduct only one trade per offer or bid, a user can decline subsequent trades. Avoiding Broken TradesPossible Order Fill Amounts and Seller Compliance Representation The present invention seeks to prevent the users ability to break trades, that is, not complete a trade after a match has been made. One possible way for a seller to break or not close a trade is when the actual carrying out of that trade would be in violation of the bank loans minimum assignment amount or minimum retained amount restrictions. If such non-closure of trades were allowed, then buyers may miss opportunities to purchase loans elsewhere possibly resulting in increased expense to the buyer. All of this in turn may result in loss of support for the system by the users themselves. To prevent the foregoing possible non-closure of trades from occurring, the system has a number of safe-guards, one of which is its confirmation process. Firstly, upon entry of an order (offer or bid), the users order is posted to that user as an order confirmation webpage, such as shown in FIG. 5. The order confirmation webpage may repeat some or most of the information that the user entered in the Bid and Offer Input page shown in FIG. 3. The order confirmation webpage further repeats the offer or bid amount with the associated fill instructions (i. e. All or None, Partial Fill, Partial Increments Only) and all of the, fill amounts that can satisfy the order. This information presented to the user ensures that the user is aware. of the possible outcomes of the order and bears most significance in the requirement that the seller represent that the minimum assignment amounts and minimum retained amounts as provided in the credit agreement are complied with. Table 4 below shows exemplary offer amounts and fill instructions that may be entered by a seller and the possible fill amounts that would be provided to the user upon entry thereof. Similarly, Table 5 below shows exemplary bid amounts and fill instructions that may be entered by a buyer and the possible fill amounts that would be provided to the user upon entry thereof. The order confirmation webpage further requires a seller to confirm that if a trade is conducted, that such trade would not be in violation of any relevant credit documents, specifically the minimum assignment amount and minimum retained amount restrictions thereof, regardless of whether the order was partially or fully filled. Since sellers already have the credit documents by virtue of their participation in the bank loan facility and buyers may not necessarily already be in the facility and have access to the credit agreement, the onus is on sellers to confirm that only amounts equal to or in excess of the minimum assignment amount can possibly be traded and any retained amount be equal to or in excess of the minimum retained amount. The order confirmation page further may request that the seller confirm the amount of the minimum assignment amount of the credit agreement, for example, by sending via facsimile a copy of the credit agreement containing such information, if such information was not already confirmed. Undisclosed Orders The present invention further allows users to place undisclosed orders within the system. Undisclosed orders (bids or offers) are identical in all respects to the previously discussed bids and offers, except they are not displayed to users (e. g. on the quote page shown in FIG. 2 ). By providing an undisclosed bid or offer, the users order will not move the price of the loan against that users position, whereas a disclosed order might move the price. Generally, when a borrower is experiencing financial or operating difficulty, the placement of an offer to sell a loan concerning that borrower may induce other potential sellers to post offers at lower prices. This disadvantageous result to the seller is prevented by placing an undisclosed order. As with disclosed orders, if an entered order matches an undisclosed order, a trade takes place. However, if a bid and an offer are within 1.5 points (or other suitably close position) of one another and one or both of the bid and offer are undisclosed, the system or, alternatively, the systems personnel determines the likelihood of a trade taking place. If a trade is likely to occur, then the two users involved are notified of the proximity of the opposing orders. The system or personnel will then negotiate with both sides to complete a trade. This additional intervention by the system advantageously results in trades that otherwise would not take place when undisclosed orders are involved. The above-discussed functions and features of confirming the order and matching of bids and offers, whether disclosed or undisclosed, with the various confirmations are further schematically illustrated in the flow chart shown in FIGS. 6A-6G. Steps 300 - 304 concern user authentication security measures. User order information is printed at step 305 and based upon whether the order is a bid or an offer, as determined at inquiry 306 . the process proceeds to step 307 for an offer and inquiry 316 ( FIG. 6B ) for a bid. Steps 307 - 310 concern compliance with the credit agreement. Inquiries 311 and 316 determine if the indicated borrower is in the system and if not, a user message is provided at step 312 . Similarly, inquiries 314 and 317 determine if the indicated tranche is in the system and if not, a user message is provided at 315 . The systems personnel is notified at step 313 . For offers, the system verifies that the grid or that the tranches base rate and base rate spread are in the system at inquiries 318 and 319 (FIG. 6 C). If not, the user is informed at step 320 . Whether the minimum assignment information is in the system is determined at inquiry 321 and if not, the user is asked to provide proof of the minimum assignment amount at request 322 . Inquiry 323 verifies that the order amount is not less than the minimum size indicated. If it is, steps 324 - 325 advise the user. Inquiry 326 ( FIG. 6D ) verifies that the minimum size indicated is not less than the minimum assignment amount. If it is, steps 327 - 328 advise the user. Steps 329 - 332 concern providing advice to the user concerning the order, if necessary. Inquiry 333 and step 334 allow the user to return to the bid and offer input webpage, if desired. At step 335 (FIG. 6 E), the order is entered into the system and at step 336 . the process for finding a match for the order begins. Inquiry 337 determines it a match exists and if so, steps 338 - 351 ( FIGS. 6E and 6F ) are carried out. If, on the other hand, no match exists, then the system determines if another similar bid or offer already exists at inquiry 352 ( FIG. 6G ) and steps 353 - 358 determine which bid is greater or offer is lower and cancels the other bid or offer. Then, if the order currently being made is accepted, inquiry 359 determines if it is an undisclosed order. If so, an inquiry is made as to whether the order is within 1.5 points of an opposing order at inquiry 361 and if so, system personnel are notified at step 363 . Disclosed orders are posted by the system at step 360 . In addition to the above-described method and facility for matching buyers with sellers of bank loans, the bank loan trading system of the present invention further utilizes electronic auctions on the lexc website (or other suitable site), as discussed below. Currently, in the bank loan market, auctions generally are conducted by the firm selling (or buying in a reverse-offer auction) the bank loan. This firm is also referred to as the sponsor of the auction. As previously mentioned, without clearly-defined rules and a third party following generally accepted or standardized procedures, many auctions are conducted with less than fair and equitable results. This in turn discourages participants from engaging in announced auctions for fear their due diligence prior to their participation will become a wasted effort. Accordingly, participants often will not participate or put their best efforts or bids into an auction. With reduced participation due to a history of poorly conducted auctions by various sponsors, sponsors likely experience lower bids or higher reverse-offers. Furthermore, since the participants in auctions are generally dealer desks, these dealers are receiving their compensation from the difference in the price paid by the dealers buyer and the bid provided to the sponsor. This further reduces the amount received or increases the amount paid by the sponsor. In accordance with the present invention, the system (via its website) provides clear rules that ensures fair and equitable execution of bank loan auctions. In addition, the system of the present invention bypasses dealers, thereby increasing the proceeds or reducing the purchase cost to the sponsor. Three types of auctions may be carried out by the present invention: standard, blind and dutch. Table 80 shown in FIG. 2 provides various information regarding currently scheduled auctions and FIG. 7 is an exemplary webpage displayed to a user who seeks to schedule an auction. FIG. 8 is an exemplary webpage displayed to a user who seeks to make a bid or offer in an auction. Standard Auctions The system of the present invention allows the user to schedule a so-called standard auction which places a bank loan for sale to the highest bidder until the gavel falls. A pre-announced start date and time and the allotted time before the gavel falls are provided by that user. At the start of the auction, the system accepts bids and continuously posts the highest bid. This type of auction remains open so long as increasing bids continue to be entered. The action closes after no new bids are received for a stated interval of time. Therefore, the system continues to conduct the auction until an amount of time, e. g. five minutes, has elapsed since the last bid was entered. During the auction, the current highest bid and the amount of time remaining (which time is reset upon receipt of a new highest bid) are posted to users. Reverse offers also are possible and operate in a similar manner. The system refreshes the information displayed to users at a rate significantly faster than the amount of time that must elapse before the auction closes, thus ensuring that the Internet-conducted auction is fair to all users. For example, the system may provide a refresh rate of 15 seconds versus 5 minutes for the period for the gavel to fall. Blind Auctions The system further allows users to schedule so-called blind auctions at a preset date and time. In a blind auction, the auction closes at a pre-announced time, but bids, including the highest bid, are not posted by the system to either the auctions participants or the sponsor of the loan. This ensures that all participants equally lack bidding information. Reverse-offer blind auctions also may be scheduled. Dutch Auctions The system also allows users to schedule dutch auctions, which are similar to blind auctions, but provide for the sale of the loan (or purchase of a loan in a reverse offer) to one or more participants. Thus, while blind auctions can be considered to be an All or None type order, Dutch auctions may be partially filled by a number of auction participants. In the Dutch auction, the auction price for all purchasers is the lowest bid made by the eventual purchasers (representing the highest bidders) or, in the case of a reverse offer, is the highest offer made by the eventual sellers (representing the lowest offerors). Table 6 below shows example bids made during a Dutch auction sale of 50 million of a loan. Participants providing Bid 1 . Bid 2 and Bid 3 would all pay 98.00. Equitable Auctions Once an auction is entered or posted by the system, it may not be removed. Sponsors are required to place a minimum acceptable bid for which they will sell their loan or a maximum acceptable offer for which they will pay for a loan in a reverse-offer auction. Thus, the sponsor is not forced to accept below-market bids or above-market offers and participants are assured that if they place a bid above the a minimum acceptable bid or an offer below the maximum acceptable offer, the sponsor cannot refuse such bid or offer if no better bid or offer exists. Therefore, the participant knows that if the minimum acceptable bid or maximum acceptable offer is reasonable, then it may not be a waste of time to conduct due diligence to participate in the auction because the auction can not be stopped prior to completion. In addition, knowing that their bid or offer can not be shopped at the end of the auction provides the participant with the knowledge that his effort to make a bid or offer will not be inappropriately used by the sponsor to achieve a better bid or offer from a favored third party. Bids and offers may be entered that fall below the designated minimum acceptable bid or above the maximum acceptable offer, respectively. In the case that the highest bid still falls below the minimum acceptable bid or the lowest offer still is above the maximum acceptable offer, the system provides the sponsor the opportunity to accept or reject the best bid or offer. The system further allows the sponsor of an auction, prior to or during the auction, to modify various criteria previously set but only if such modification increases the likelihood of a completed trade. The system allows the sponsor to decrease its minimum acceptable bid and, similarly, to increase its maximum acceptable offer. Such changes could only tend to increase the likelihood of a successful, completed trade. Increasing the minimum acceptable bid or decreasing the maximum acceptable offer disadvantageously decreases the likelihood of a completed trade and thus is forbidden. The system further allows participants in an auction to only increase their bids or decrease their offers (in a reverse-offer). In dutch auctions, participants can also increase the dollar amount tendered, but not decrease it. Auctions Must Comply with Credit Agreement Whether the sponsor or the participant is the seller in a sale auction or reverse-offer auction, respectively, the system requires the seller to represent its compliance with the minimum assignment and retained amounts restrictions of the credit agreement. FIG. 9 is an exemplary webpage displayed to a user sponsoring and participating in an auction that requires the user to certify that it complies with these restrictions of the credit agreement. System Analytics and Sorting Capability In addition to the foregoing matching of sellers and buyers of bank loans and bank loan auctions, the system of the present invention further allows users thereof to arrange the aforementioned bank loan data, including the offers and bidders thereof, in different manners on the users computer monitors. FIG. 10 is an exemplary so-called analytics webpage that can be displayed to a user. Table 90 shown in FIG. 10 is similar to table 20 shown in FIG. 2. but table 90 is adapted for the purpose of comparing posted loans in different manners. For example, loans shown in table 90 can be sorted using any column therein as the sorting criteria. Thus, loans can be sorted chronologically depending on their quarter ending date, loans can be sorted numerically based on their total yield to an assumed maturity date (chosen as a percentage of time until maturity), and so on. For the sort on the yield, the system can assume the loan is outstanding for only 50 of the stated time until maturity. Therefore a premium or discount is amortized in half the amount of time, thereby reducing or increasing the yield, respectively. Given this feature of the present invention, users are able to quickly and easily obtain useful information helpful in their decision to make appropriate bids and offers. In accordance with a further embodiment of the present invention, the disclosed system and corresponding method may be applied to the trading of bonds whereby setting matching rules or utilizing auctions could increase the liquidity for, or in other words increase the number of buyers and sellers interested in, the trading of bonds. Since most bonds are traded over-the-counter, therefore through dealers acting as middlemen rather than through exchanges, and the trading in any particular issue of bond is generally not as active as with stocks, there are generally a limited number of dealers through which an investor can buy or sell the desired bonds. Due to this lack of trading in any given bond, the cost of execution is generally more expensive for bonds than stocks due to a lack of liquidity or demand for secondary purchases of the bonds. Therefore dealers acting as middlemen have to spend more time and effort to execute transactions. In addition, with limited competition and limited publication of market prices, the dealers may charge a large amount or excessive mark-up for trade execution. With the present invention applied to bonds, execution could be significantly more efficient as the number of potential buyers or sellers could increase and contacting these investors would be less expensive, thereby reducing the cost of execution. Furthermore, the rounding and matching method described in the present invention could increase the number of trades executed as it provides a method for matching buyers and sellers of unusual amounts and sizes. For example, bonds are typically issued in amounts of 1,000 per bond and trade in multiples of 100,000 or 100 bonds. If a seller has 231 bonds (worth 231,000), utilizing rules similar to that for bank loans whereby the buyers are subject to having their bids filled in odd amounts, the seller may sell its bonds to a buyer who placed a bid for 200 bonds plus or minus 50 bonds. Therefore, the rounding mechanism could increase the liquidity for odd-size trades of bonds. Further, an announced auction may increase interest in any particular sale or reverse-offer purchase of bonds. Similarly, the present invention may be applied to the trading of large blocks of stocks where the utilization of existing bid and offer systems on exchanges may cause large order imbalances that significantly and adversely impact the sale price. Exchanges will typically display bids and offers for stock up to amounts of 1,000,000 for example. If an order were placed for 5,000,000 or more, the sheer size of this order may move the market price against the party placing the order. Block trades are therefore typically conducted through block trading desks of broker-dealers. Similar to trading bonds over the counter, utilizing these block trading desks may result in expensive execution as the large amount of the trade may require an extensive effort and. large risk to resell the large position. Therefore, like the trading of bonds, utilizing the disclosed system and either the auction method or the rounding and matching method in accordance with the present invention may be more efficient and less expensive than the current method of trading though dealers block trading desks. Another possible application of the present invention is to the trading of odd lots of stocks. Stock trades are usually executed in amounts of 100 shares of stock. The present invention could apply the rounding and matching method previously discussed to post even amounts of the number of shares that may lead to the filling of odd-size number of share trades The linked order aspect of the present invention could be used to allow sellers to post very specific alternative fill instructions for stocks and bonds. T. ex. a seller may wish to sell only either 1,000,000 of bonds or 750,000 of bonds. This could be accomplished with a linked order of 1,000,000 All or None and 750,000 All or None. The systems auction function could also be applied to other financial assets. In other markets where the financial assets may be somewhat illiquid, therefore there may not be a competitive bid for all specific assets for sale, sellers may wish to sell the specific asset by way of auction. This applies especially to large financial assets sales where the dutch auction method described herein would allow a large sale to be divided into small portions allowing for better execution of the sale. In addition to the auctioning of financial assets, the present invention can be applied to the auctioning of non-financial assets. For both financial and non-financial assets, the present invention solves two issues at once. First, auctions with displayed prices and fixed end times create a rush to bid near the end time. By having a fixed end time, higher bids that may have been submitted given more time (or an open end until the gavel falls) would be prevented. Second, on-line auctions create an environment allowing for more participants, especially as most participants are not in the business of traveling to participate in small or one-off auctions. If a displayed-price auction is desired, then an on-line, open-ended auction would reach the most participants and generate the best bid because of (1) not preventing a higher bid (as discussed above), and (2) encouraging more participants such that more participants generates more bids, which generally will generate a higher highest bid in the long run. While the present invention has been particularly shown and described in conjunction with preferred embodiments thereof, it will be readily appreciated by those of ordinary skill in the art that various changes may be made without departing from the spirit and scope of the invention. For example, although the present invention has been described with respect to the trading and auctioning of bank loans, the present invention is not limited solely thereto and may be widely applied to the trading and auctioning of other financial interests within the secondary market, such as real estate and project finance loans As another example, although the present invention has been described as being a functional website on the Internet, the present invention suitably may be applied to intranets or even the non-computer forum. Therefore, it is intended that appended claims be interpreted as including the embodiments described herein, the alternatives mentioned above and all equivalents thereto.