Bayesian Inference for the Jump-Diffusion Model with M Jumps |
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| Authors: | Maciej Kostrzewski |
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| Institution: | 1. Faculty of Management, Cracow University of Economics, Cracow, Poland;2. Faculty of Applied Mathematics, AGH University of Science and Technology, Cracow, Poland |
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| Abstract: | In this article, we propose a new class of models—jump-diffusion models with M jumps (JD(M)J). These structures generalize the discretized arithmetic Brownian motion (for logarithmic rates of return) and the Bernoulli jump-diffusion model. The aim of this article is to present Bayesian tools for estimation and comparison of JD(M)J models. Presented methodology is illustrated with two empirical studies, employing both simulated and real-world data (the S&P100 Index). |
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| Keywords: | Bayesian inference Mixture of normal distributions MCMC methods Merton model Jump-diffusion processes Bernoulli jump-diffusion model Latent variables |
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