Abstract

This chapter discusses Markov Chain Monte Carlo (MCMC) based methods for estimating continuous-time asset pricing models. We describe the Bayesian approach to empirical asset pricing, the mechanics of MCMC algorithms and the strong theoretical underpinnings of MCMC algorithms. We provide a tutorial on building MCMC algorithms and show how to estimate equity price models with factors such as stochastic expected returns, stochastic volatility and jumps, multi-factor term structure models with stochastic volatility, time-varying central tendancy or jumps and regime switching models.

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Citation

Johannes, Michael, and Nicholas Polson. "MCMC Methods for Financial Econometrics." In Handbook of Financial Econometrics 2, 1-72. Ed. Y. Ait-Sahalia and L.P. Hansen. Amsterdam: North Holland, May 2009.

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