Improved algorithms for basket default swap valuation

• Main Authors: Chan, Yi-Lun, 詹依倫
• Other Authors: 劉惠美
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/77378164175064605029

碩士 === 國立政治大學 === 統計研究所 === 97 === Credit default swap (CDS) is the most popular in many kinds of credit derivatives, but number of obligor couldn’t be one always because of the expansions of financial market and contracts. CDS which has been contained more than one obligor is called basket default swap (BDS). According to Chiang et al. ((2007), Journal of Derivatives, 8-19.), applying importance sampling to estimate the default payment in one factor model could not only guarantee the default event occurs but also improve the efficiency of estimation. So this paper extends this concept for expanding this method to multiple factors model. There are three methods for expanding: First, merge multiple factors into a marginal factor and apply importance sampling to this marginal factor; second, apply importance sampling to the factor which has higher factor loading and third, we consider portfolio C in Glasserman ((2004), Journal of Derivatives, 24-42.) and divide total obligors into two independent groups. We would use the ways of exponential twist and the method in one factor model of Chiang et al. (2007) considered in two parts to raise the probability of default event occur. Borrow by the result of numerical simulation, method 1 has better results when obligors are homogeneous model; the results of method 2 are outstanding in each model, but its efficiency is worse and the procedure doesn’t fit with the realistic financial situation; the third method is the application of the special model, it could only apply to the model which could separate obligors independently, and the accuracy of estimates is strongly correlated to the position of exponential twist. In section 4, we would display the estimator and variance reduction in two different positions.