Fixed income modeling

What kinds of fixed income Excel models are used in trading/research? Is it usually just basic duration/PV01 stuff or something more complex? If anyone has a sample model they could share via PM or name some book/website that goes over any such model, that'd be great too.

Thanks, any insight is appreciated.

 
Best Response
FrankD'anconia:

Binomial interest rate trees and monte carlo simulation for RMBS. I can't really speak as to whether or not they're commonly used though.

They are in research. (According to the few people I actually know in MBS research)

It really depends on what kind of FI you are talking about. As was said in the post above me, monte carlo simulations are used for mortgage backed securities, but not really in corporates or gov. debt. For additional modelling in credit research, you are using your basic 3-statement models etc. Credit research actually looks a lot like equity research, you are just focusing on different metrics and downside vs. upside.

Actually pricing bonds is where the different models come in. You have your DCF and tie it to a binomial tree and your target yield curve (or spot or forward w/e).

Again, want to reiterate, this is all just second hand from what I have gathered from speaking with a couple guys in FI trading and research.

 
BrokenIncome:
Thats kind of a broad question, to say the least.

What is the most commonly used model, and are different models used for different fixed income securities (bonds, CDOs, etc...)

 

Jimbo, I'm only familiar with the Black and Hull White models-- can you please explain the cheyette and gbm models to me (or link to some papers) and the general idea of how their dynamics are different from the admittedly very simple movements of the ones I listed above? (ps i'm taking a grad-level stat course this semester so feel free to be esoteric)

 

I think models are asset-specific in structured land. For instance, expected losses for ABS models seem to be more econometric cross-sections. Market implied approaches rely heavily on time series. CDO are usually normal copula driven, though approaches still vary significantly. Tweaks like jumps or transformations are common, but the basics usually seem consistent. These results are used in conjunction with other models for appropriate risks (IR, FX, prepay, transitions, etc.) to get pricing.

Whether of not any of these are appropriate is another issue. Pricing for risk is very different than pricing for profit. Idiosyncracies and structural characteristics make apples difficult to find in some markets, I suspect.

 

Devin, it's beyond the scope of this forum. Cheyette is one of the simplest skew enabled models. Google Cheyette CEV and you'll get something.

BGM is better at capturing vols and correlations in general, and it's used frequently for rate exotics....it's monte carlo based and for callable structures can be pretty computationally intensive, especially b/c you have to also run longstaff-schwartz or something similar to determine exercise strategies and boundaries for the berm.

http://papers.ssrn.com/sol3/papers.cfm?abstract_id=427084

 

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