Extracting volatility signal using maximum a posteriori estimation

David Neto

Physica A: Statistical Mechanics and its Applications, 2016, vol. 461, issue C, 788-794

Abstract: This paper outlines a methodology to estimate a denoised volatility signal for foreign exchange rates using a hidden Markov model (HMM). For this purpose a maximum a posteriori (MAP) estimation is performed. A double exponential prior is used for the state variable (the log-volatility) in order to allow sharp jumps in realizations and then log-returns marginal distributions with heavy tails. We consider two routes to choose the regularization and we compare our MAP estimate to realized volatility measure for three exchange rates.

Keywords: Hidden Markov model; Volatility; Maximum a posteriori estimator; IDM algorithm; Laplace process; Realized volatility (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:461:y:2016:i:c:p:788-794

DOI: 10.1016/j.physa.2016.05.065

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