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    政大機構典藏 > 商學院 > 金融學系 > 期刊論文 >  Item 140.119/64950


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    题名: Empirical Performance and Asset Pricing in Hidden Markov Model
    作者: Fuh, Cheng-Der;Hu, Inchi;Lin, Shih-Kuei
    林士貴
    贡献者: 金融系
    关键词: Markov switching model;Stochastic volatility model;Leptokurtic;Cluster phenomenon;Long memory;Volatility smile;European options;Likelihood estimation;EM algorithm
    日期: 2003
    上传时间: 2014-03-27 17:04:17 (UTC+8)
    摘要: To improve the empirical performance of the Black-Scholes model, many alternative models have been proposed to address leptokurtic feature, volatility smile, and volatility clustering effects of the asset return distributions. However, analytical tractability remains a problem for most alternative models. In this article, we study a class of hidden Markov models including Markov switching models and stochastic volatility models, that can incorporate leptokurtic feature, volatility clustering effects, as well as provide analytical solutions to option pricing. We show that these models can generate long memory phenomena when the transition probabilities depend on the time scale. We also provide an explicit analytic formula for the arbitrage-free price of the European options under these models. The issues of statistical estimation and errors in option pricing are also discussed in the Markov switching models.
    關聯: Communications in Statistics: Theory and Methods,32(12), 2477-2512
    数据类型: article
    显示于类别:[金融學系] 期刊論文

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