Looking for someone who has a programming background who can take a data feed showing mortgage bond prices in dollars and convert it to yield (also known as BEY / interest rate) I am not familiar with the exact financial conversion calculation as mortgage bonds mature differently than typical bonds and have their own function, but I can provide a link to a comprehensive book and also data which would allow you to determine if your calculations are right.
I would like this delivered in as a DLL that can be used in .Net environment and (if possible) would also like comprehensive tables/matricies that can provide a conversion factor for a given price, at a given coupon value, and maturity date.
Here is a comprehensive book on Bonds and their calculations. To convert the BID into BEY we need a mortgage backed security formula [login to view URL]
Below is a sample file showing the "BID BEY" percent. This is derived from the "BID" the "COUPON", and "TERM". Our new data file does not have "BID BEY" hence this requirement.
"ITEM","RIC","STUB","TERM","COUPON","MONTH","DATE","TIME","BID","ASK","BID BEY"
"FNMA 3.000 03","MBFNR3.000F360M1","MBFNR","360","3.000","03","03-Mar-2014","20:45","97.47100052","97.50225052","3.32810184"
"FNMA 3.000 04","MBFNR3.000F360M2","MBFNR","360","3.000","04","03-Mar-2014","20:45","97.25463721","97.28588721","3.36008961"
"FNMA 3.500 03","MBFNR3.500F360M1","MBFNR","360","3.500","03","03-Mar-2014","20:45","101.68263727","101.71388727","3.21754260"
"FNMA 3.500 04","MBFNR3.500F360M2","MBFNR","360","3.500","04","03-Mar-2014","20:45","101.38722888","101.41847888","3.26051515"
"FNMA 4.000 03","MBFNR4.000F360M1","MBFNR","360","4.000","03","03-Mar-2014","20:45","105.07568431","105.10693431","3.12133508"
"FNMA 4.000 04","MBFNR4.000F360M2","MBFNR","360","4.000","04","03-Mar-2014","20:45","104.75683425","104.78808425","3.17084469"
"FNMA 4.500 03","MBFNR4.500F360M1","MBFNR","360","4.500","03","03-Mar-2014","20:45","107.53835518","107.56960518","3.03831529"
"FNMA 4.500 04","MBFNR4.500F360M2","MBFNR","360","4.500","04","03-Mar-2014","20:45","107.32921160","107.36046160","3.07351242"
"FNMA 5.000 03","MBFNR5.000F360M1","MBFNR","360","5.000","03","03-Mar-2014","20:45","109.65287647","109.68412647","2.81450937"
"FNMA 5.000 04","MBFNR5.000F360M2","MBFNR","360","5.000","04","03-Mar-2014","20:45","109.38964950","109.42089950","2.86556032"
"FNMA 5.500 03","MBFNR5.500F360M1","MBFNR","360","5.500","03","03-Mar-2014","20:45","110.42266977","110.45391977","2.99724700"
"FNMA 5.500 04","MBFNR5.500F360M2","MBFNR","360","5.500","04","03-Mar-2014","20:45","110.28041332","110.31166332","3.02545462"
"FNMA 6.000 03","MBFNR6.000F360M1","MBFNR","360","6.000","03","03-Mar-2014","20:45","111.48799948","111.51924948","3.22619766"
"FNMA 6.000 04","MBFNR6.000F360M2","MBFNR","360","6.000","04","03-Mar-2014","20:45","111.25433566","111.28558566","3.27345497"
"FNMA 6.500 03","MBFNR6.500F360M1","MBFNR","360","6.500","03","03-Mar-2014","20:45","111.85107402","111.88232402","2.78115443"
"FNMA 6.500 04","MBFNR6.500F360M2","MBFNR","360","6.500","04","03-Mar-2014","20:45","111.78429474","111.81554474","2.79708411"
"GOLD 3.000 03","MBFRR3.000F360M1","MBFRR","360","3.000","03","03-Mar-2014","20:45","97.26419233","97.29544233","3.37057557"
"GOLD 3.000 04","MBFRR3.000F360M2","MBFRR","360","3.000","04","03-Mar-2014","20:45","97.00912823","97.04037823","3.40855593"
"GOLD 3.500 03","MBFRR3.500F360M1","MBFRR","360","3.500","03","03-Mar-2014","20:45","101.42194391","101.45319391","3.26887362"
"GOLD 3.500 04","MBFRR3.500F360M2","MBFRR","360","3.500","04","03-Mar-2014","20:45","101.15369784","101.18494784","3.30842611"
"GOLD 4.000 03","MBFRR4.000F360M1","MBFRR","360","4.000","03","03-Mar-2014","20:45","104.82531706","104.85656706","3.17484503"