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计量、金融与大数据分析workshop：A general option pricing framework for affine fractionally integrated models
发布日期：2024-07-24 12:00 来源：
题目: A general option pricing framework for affine fractionally integrated models
摘要: This article studies the impact of fractional integration on volatility modelling and option pricing. We propose a general discrete-time pricing framework based on affine multi-component volatility models that admit ARCH(∞) representations. This not only nests a large variety of option pricing models from the literature, but also allows for the introduction of novel covariance-stationary long-memory affine GARCH pricing models. Using an infinite sum characterization of the log-asset price's cumulant generating function, we derive semi-explicit expressions for the valuation of European-style derivatives under a general variance-dependent stochastic discount factor. Moreover, we carry out an extensive empirical analysis using returns and S&P500 options over the period 1996-2019. Overall, we find that once the informational content from options is incorporated into the parameter estimation process, the inclusion of fractionally integrated dynamics in volatility is beneficial for improving the out-of-sample option pricing performance. The largest improvements in the implied volatility root-mean-square errors occur for options with maturities longer than one year, reaching 33\% and 13\% when compared to standard one- and two-component short-memory models, respectively.
主讲人：Alexandru Badescu (University of Calgary)
主持人：黄卓
时间：2024年7月24日（周三） 15:00 – 16:30
地点：北京大学国家发展研究院（承泽园）333会议室
主讲人简介：Alexandru Badescu is a professor in the Department of Mathematics and Statistics at the University of Calgary. His research interests lie in Financial mathematics, Finance time series analysis, Actuarial science, and Machine Learning. Professor Badescu has published papers in Journal of Econometrics, Journal of Financial Econometrics, Journal of Economic Dynamics and Control, Insurance: Mathematics and Economics, European Journal of Operational Research, Journal of Futures Markets, Quantitative Finance.
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计量、金融与大数据分析workshop：A general option pricing framework for affine fractionally integrated models
发布日期：2024-07-24 12:00 来源：
题目: A general option pricing framework for affine fractionally integrated models
摘要: This article studies the impact of fractional integration on volatility modelling and option pricing. We propose a general discrete-time pricing framework based on affine multi-component volatility models that admit ARCH(∞) representations. This not only nests a large variety of option pricing models from the literature, but also allows for the introduction of novel covariance-stationary long-memory affine GARCH pricing models. Using an infinite sum characterization of the log-asset price's cumulant generating function, we derive semi-explicit expressions for the valuation of European-style derivatives under a general variance-dependent stochastic discount factor. Moreover, we carry out an extensive empirical analysis using returns and S&P500 options over the period 1996-2019. Overall, we find that once the informational content from options is incorporated into the parameter estimation process, the inclusion of fractionally integrated dynamics in volatility is beneficial for improving the out-of-sample option pricing performance. The largest improvements in the implied volatility root-mean-square errors occur for options with maturities longer than one year, reaching 33\% and 13\% when compared to standard one- and two-component short-memory models, respectively.
主讲人：Alexandru Badescu (University of Calgary)
主持人：黄卓
时间：2024年7月24日（周三） 15:00 – 16:30
地点：北京大学国家发展研究院（承泽园）333会议室
主讲人简介：Alexandru Badescu is a professor in the Department of Mathematics and Statistics at the University of Calgary. His research interests lie in Financial mathematics, Finance time series analysis, Actuarial science, and Machine Learning. Professor Badescu has published papers in Journal of Econometrics, Journal of Financial Econometrics, Journal of Economic Dynamics and Control, Insurance: Mathematics and Economics, European Journal of Operational Research, Journal of Futures Markets, Quantitative Finance.
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