【摘 要】
：
Asset pricing and volatility modeling take a center stage in financial econometrics.This talk concerns calibration of stochastic volatility models via Marko
【机 构】
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University of North Carolina
【出 处】
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2009 International Conference on Financial Statistics and Fi
论文部分内容阅读
Asset pricing and volatility modeling take a center stage in financial econometrics.This talk concerns calibration of stochastic volatility models via Markov chain Monte Carlo (MCMC) methods based on returns and option data.With the presence of high-dimensional latent volatility processes,numerical integration for computing option prices is required at every time point and every iteration of MCMC.There is an urgent need for developing approximation schemes that reduce numerical integration from a high-dimensional space (of diffusion sample paths) to a low-dimensional space (of 2D or 3D random vectors).
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