I have attempted to replicated the bloomberg CDSW screen and DV01 calculations but have fallen short. Assume flat swap rates: 4.75% Flat CDS curve [5Y]: 65bpsRecovery: 40%Using DV01=(1-exp(-(r+h)*t))/(r+h) I got *4.382*Using DV01= SUM [DF(i)*Sp(i)*alpha(i)] I got *3.753* using 79.29% Discount Factor, .9467 Surv Prob and 5Y time .. note my def. prob. here assumes .0533 vs .055 via BBERG. BBERG gives 4.44 albeit it uses a BGN swap curve which I assume to be flat. Any other suggestions or is the first one the quick/dirty way to go?

QuoteOriginally posted by: waiter222I have attempted to replicated the bloomberg CDSW screen and DV01 calculations but have fallen short. Assume flat swap rates: 4.75% Flat CDS curve [5Y]: 65bpsRecovery: 40%Using DV01=(1-exp(-(r+h)*t))/(r+h) I got *4.382*Using DV01= SUM [DF(i)*Sp(i)*alpha(i)] I got *3.753* using 79.29% Discount Factor, .9467 Surv Prob and 5Y time .. note my def. prob. here assumes .0533 vs .055 via BBERG. BBERG gives 4.44 albeit it uses a BGN swap curve which I assume to be flat. Any other suggestions or is the first one the quick/dirty way to go?What are you using for time? Don't forget that the for a five year the maturity is currently 20/09/2012, which when calculated on an actual/360 basis should give you a pretty close answer - I will do a test when I'm next in work.

Your formula doesn't take into account the expected accrued coupon to be potentially paid till default time.Not sure about BBG, but they might have included a correction to include this factor that can be quite significant for higher yielding names.Hope it helpsS

This is the approximation we usehttp://www.noelwatson.com/blog/PermaLink,guid, ... 9a548.aspx

Noel - i wasn't able to open the program you pic'ed on your site, But it looks like you used the formula:double DV01 = (1-Math.Exp(-((interestRate+hazardRate)*timeToMaturity)))/(interestRate+hazardRate)*notional*100Same as mine below. PS, I like your site. Stefanone - good point.

This formula assumes coupon is paid continoulsy which is not the case in the real world.What people do is to discount coupon leg with quarterly payments and then add a correction term to take into account the expected accrued interest. I think your difference is coming probably from this.

Ok - cool. thanks for the help SG

One thing I've never understood is the relationship between the probability of default/survival and the recovery rate. I've never much liked the JPM paper because it over complicates something rather simple that can be explained intuitively. Yet there P(D) as well as a MER paper I read are a function of a hazard rate. Yet in the same paper they go on to show graphs of the different survial curves (time on x axis, probability on y axis) for different recovery rates (curves of various convexity). Now, I've never seen a paper which relates the two in a mathematical and intuitive way. For me the cumulative P(S) = exp(-ht) where h is the hazard rate and t time. It is not a function of R so how do they plot those graphs? Am I missing something, but to me and the alegbra I know from the original paper, R is simply acts as a scalar to compute the expected loss. This will affect the ultimate spread but not the underlying probabilities. Can someone please help?

QuoteOriginally posted by: CreditJediOne thing I've never understood is the relationship between the probability of default/survival and the recovery rate. I've never much liked the JPM paper because it over complicates something rather simple that can be explained intuitively. Yet there P(D) as well as a MER paper I read are a function of a hazard rate. Yet in the same paper they go on to show graphs of the different survial curves (time on x axis, probability on y axis) for different recovery rates (curves of various convexity). Now, I've never seen a paper which relates the two in a mathematical and intuitive way. For me the cumulative P(S) = exp(-ht) where h is the hazard rate and t time. It is not a function of R so how do they plot those graphs? Am I missing something, but to me and the alegbra I know from the original paper, R is simply acts as a scalar to compute the expected loss. This will affect the ultimate spread but not the underlying probabilities. Can someone please help?...well..your market data is the quoted spread, so from that data and the recovery (typical assumption: fixed recovery) you have to obtain the hazard rate. Imagine a single period CDS: if Dflt Occurs you pay 1-R at Mty, otherwise you received the spread pymnt at Mty. neglecting dyacount fraction and discount factors and assuming your reference is alive today you will Get something like the following expresion to calculate the breakeven spread: NPV = 0 = S*P-(1-R)*(1-P) P beeing survival probability up to Mty. this way you get P = 1/(1+S/(1-R)) so P = f(S,R) and so is your hazard rate. Note that S is your market data...you know it so you are left with a function of the assumed recoverydoe this solve your doubt?

Thanks! I get it; what I was doing when I bootstrapped was to solve the year 1 P(D) such that the two legs of the swap (as defined by JPM) equated. I'll have a play with some numbers in a spreadsheet and see what I find