Gibbs Sampling Approach to Markov Switching Models in Finance

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Gibbs Sampling Approach to Markov Switching Models in Finance

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ABSTRACT

In the present paper we apply the Gibbs Sampling approach to estimate the parameters of a Markov Switching Model which we use to model financial time series. In particular, we estimate the standard deviation of the time series in order to obtain an indicator similar to the VIX index. The Markov Switching technique has been chosen because of the presence of exogenous factors which can have a large impact on the market, making it behave differently in different time periods. We also perform a case study on the S&P500 index for the period 3 January, 2007 - 29 December, 2014.

KEYWORDS

Markov Switching, α-stable Distribution, Gibbs Sampling, Finance, Financial time series

REFERENCES

[1] Di Persio, L. , Frigo, M. ”Gibbs sampling approach to regime switching analysis of financial time series.” Journal of Computational and Applied Mathematics (2016). [1] Di Persio, L. , Frigo, M. ”Gibbs sampling approach to regime switching analysis of financial time series.” Journal of Computational and Applied Mathematics (2016).

[2] Di Persio, L. , Frigo, M. ”Maximum Likelihood Approach to Markov Switching Models.”, WSEAS Transactions on Business and Economics, , Volume 12, 2015, Art.21, pp. 239-242

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Cite this paper

Luca Di Persio, Vukasin Jovic. (2016) Gibbs Sampling Approach to Markov Switching Models in Finance. International Journal of Mathematical and Computational Methods, 1, 182-185