TY - JOUR
T1 - Estimation and evaluation of the term structure of credit default swaps
T2 - An empirical study
AU - Chen, Ren Raw
AU - Cheng, Xiaolin
AU - Liu, Bo
PY - 2008/12
Y1 - 2008/12
N2 - Chen, Cheng, Fabozzi and Liu [Chen, Ren-Raw, Cheng, Xiaolin, Fabozzi, Frank, Liu, Bo, 2008. An explicit, multi- factor credit default swap pricing model with correlated factors. J. Financial Quantitative Anal. 43 (1), 123-160] provide an explicit solution to the value of the credit default swap when the interest rate and the hazard rate are correlated. They also provide empirical evidence to support the model with transaction prices. In this paper, we extend their empirical work to study the term structure of CDS spreads by using a matrix CDS dataset from J. P. Morgan Chase. Matrix data contain interpolated prices based on traders' expectations, which are often criticized as being "unreal". However, the benefit of this matrix dataset is that it contains the entire credit spread curves, which allows us to understand the cross-sectional variation of the credit risk. The empirical results show that the parameters of the model are highly significant and it captures most of the cross-sectional as well as time series variation.
AB - Chen, Cheng, Fabozzi and Liu [Chen, Ren-Raw, Cheng, Xiaolin, Fabozzi, Frank, Liu, Bo, 2008. An explicit, multi- factor credit default swap pricing model with correlated factors. J. Financial Quantitative Anal. 43 (1), 123-160] provide an explicit solution to the value of the credit default swap when the interest rate and the hazard rate are correlated. They also provide empirical evidence to support the model with transaction prices. In this paper, we extend their empirical work to study the term structure of CDS spreads by using a matrix CDS dataset from J. P. Morgan Chase. Matrix data contain interpolated prices based on traders' expectations, which are often criticized as being "unreal". However, the benefit of this matrix dataset is that it contains the entire credit spread curves, which allows us to understand the cross-sectional variation of the credit risk. The empirical results show that the parameters of the model are highly significant and it captures most of the cross-sectional as well as time series variation.
UR - http://www.scopus.com/inward/record.url?scp=56549102335&partnerID=8YFLogxK
U2 - 10.1016/j.insmatheco.2008.05.005
DO - 10.1016/j.insmatheco.2008.05.005
M3 - 文章
AN - SCOPUS:56549102335
SN - 0167-6687
VL - 43
SP - 339
EP - 349
JO - Insurance: Mathematics and Economics
JF - Insurance: Mathematics and Economics
IS - 3
ER -