政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/64950

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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

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/64950

Title:	Empirical Performance and Asset Pricing in Hidden Markov Model
Authors:	Fuh, Cheng-Der;Hu, Inchi;Lin, Shih-Kuei 林士貴
Contributors:	金融系
Keywords:	Markov switching model;Stochastic volatility model;Leptokurtic;Cluster phenomenon;Long memory;Volatility smile;European options;Likelihood estimation;EM algorithm
Date:	2003
Issue Date:	2014-03-27 17:04:17 (UTC+8)
Abstract:	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.
Relation:	Communications in Statistics: Theory and Methods,32(12), 2477-2512
Data Type:	article
Appears in Collections:	[金融學系] 期刊論文

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