Correlated Default Modeling with a Forest of Binomial Trees

Posted: 9 Mar 2011 Last revised: 14 Mar 2011

See all articles by Santhosh Bandreddi

Santhosh Bandreddi

affiliation not provided to SSRN

Sanjiv Ranjan Das

Santa Clara University - Leavey School of Business

Rong Fan

Gifford Fong Associates

Date Written: October 29, 2007

Abstract

This paper exploits the endogenous default function framework of Das and Sundaram (2007) to develop an approach for modeling correlated default on binomial trees usually used for pricing equity options. We show how joint default contracts may be valued on these trees. The model accommodates different correlation assumptions and practical implementation considerations. Credit portfolio characteristics are examined within the model and found to be consistent with stylized empirics. Risk premia for default are computable and shown to be relatively higher for poor quality firms. Equity volatility is shown to impact correlated credit loss distributions substantially. Two kinds of default dependence are explored, one coming from default intensity correlations, and the other from further conditional dependence in defaults after accounting for intensity correlations (residual copula correlation). Both are found to impact credit loss distributions, though the absence of either makes these distributions less sensitive to correlation assumptions; on balance intensity correlations are more critical.

Suggested Citation

Bandreddi, Santhosh and Das, Sanjiv Ranjan and Fan, Rong, Correlated Default Modeling with a Forest of Binomial Trees (October 29, 2007). Journal of Fixed Income, Winter 2007, Available at SSRN: https://ssrn.com/abstract=1781167

Santhosh Bandreddi

affiliation not provided to SSRN

Sanjiv Ranjan Das (Contact Author)

Santa Clara University - Leavey School of Business ( email )

Department of Finance
316M Lucas Hall
Santa Clara, CA 95053
United States

HOME PAGE: http://srdas.github.io/

Rong Fan

Gifford Fong Associates ( email )

3658 Mt. Diablo Blvd.
Suite 200
Lafayette, CA 94549
United States
925-299-7800 (Phone)

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