Abstract

http://ssrn.com/abstract=1628036
 
 

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A Binomial Zero Coupon Model of Expected Bond Returns Term Structure


Zvika Afik


Ben Gurion University

Simon Benninga


Tel Aviv University - Faculty of Management

June 12, 2010


Abstract:     
We propose, analyze, and implement a model for the estimation of zero-coupon expected bond returns (EBR), expanding the model developed by Afik and Benninga (AB, 2010). The central idea of AB is to use the matrix of rating transitions to estimate a Markov model of the EBR. Unlike AB, this paper presents a tree like model that can be used to aggregate market data for each rating category and extract its zero-coupon term structure of EBR and its yield risk premium components, including a certainty equivalence premium which is related to the systematic risk of the CAPM.

We use corporate bond transaction data from the United States and a rating agency transition matrix to extract the term structure of EBR and its components and the term structure of risk-neutral default probabilities. We then apply our model and its results to the estimation of CDS premium term structure and implement it on our US bond market data set.

We believe this model can be extended and applied to a variety of research and practical purposes. A few early examples are included in our forthcoming papers on implied recovery rates, abnormal returns and premia, and market implied bond rating.

Keywords: expected returns, corporate bonds, credit risk, CDS

JEL Classification: G12, G24, G32, G33

working papers series


Not Available For Download

Date posted: June 22, 2010  

Suggested Citation

Afik, Zvika and Benninga, Simon, A Binomial Zero Coupon Model of Expected Bond Returns Term Structure (June 12, 2010). Available at SSRN: http://ssrn.com/abstract=1628036 or http://dx.doi.org/10.2139/ssrn.1628036

Contact Information

Zvika Afik (Contact Author)
Ben Gurion University ( email )
Simon Benninga
Tel Aviv University - Faculty of Management ( email )
P.O. Box 39010
Ramat Aviv, Tel Aviv, 69978
Israel
+972-3-640-6317 (Phone)
+972-2-673-4675 (Fax)
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