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Estimation of Stable Distribution and Its Application to Credit Risk

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dc.contributor.advisor Kim, Aaron en_US
dc.contributor.advisor Rachev, Svetlozar Zari en_US
dc.contributor.author Mo, Hua en_US
dc.contributor.other Department of Applied Mathematics and Statistics en_US
dc.date.accessioned 2017-09-20T16:42:29Z
dc.date.available 2017-09-20T16:42:29Z
dc.date.issued 2016-12-01 en_US
dc.identifier.uri http://hdl.handle.net/11401/76150 en_US
dc.description 78 pgs en_US
dc.description.abstract To capture the heavy tails and the volatility clustering of asset returns is always an important topic in Â…nancial market. We studies two projects related to the Alpha Stable distribution and Classical Tempered Stable(CTS) distribution respectively which both have desired properties to accommodate heavy-tails and capture skewness in Â…nancial series. (1) In the major part of the Â…rst project, we introduce the algorithm of indirect inference method. By using the skewed-t distribution as an auxiliary model which is easier to handle, we can estimate the parameters of the Alpha Stable distribution since these two models have the same numbers of parameters and each of them plays a similar role. We also estimate of the parameters of the alpha stable distribution with McColloch method, Characteristic Function Based method and MLE method respectively. Finally, we provide an empirical application on S&P 500 returns and make comparisons between these four methods. (2) In the second project, we discuss the Gaussian Â…rm value model and the Classical Tempered Stable Â…rm value model. By pointing out the drawbacks of application of MertonÂ’s model on Â…rm value, we introduce the classical tempered stable distribution and make the market Â…rm value process follows a CTS distribution instead of Gaussian distribution. We estimate the parameters of the CTS, and calculate the Â…rm value and default probability. By comparing these two models, the results suggest that CTS Â…rm value model has a better potential to predict the default probability of a Â…rm since it can better capture the heavy tails of the asset returns. en_US
dc.description.sponsorship This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree. en_US
dc.format Monograph en_US
dc.format.medium Electronic Resource en_US
dc.language.iso en_US en_US
dc.publisher The Graduate School, Stony Brook University: Stony Brook, NY. en_US
dc.subject.lcsh Finance en_US
dc.subject.other Alpha Stable Distribution, Classical Tempered Stable Distribution, Firm Value Model, Indirect Inference, Merton Model en_US
dc.title Estimation of Stable Distribution and Its Application to Credit Risk en_US
dc.type Dissertation en_US
dc.mimetype Application/PDF en_US
dc.contributor.committeemember Rachev, Svetlozar en_US
dc.contributor.committeemember Kim, Aaron en_US
dc.contributor.committeemember Glimm, James en_US
dc.contributor.committeemember Xiao, Keli en_US

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