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Markov Switching Models in Empirical Finance

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  • Massimo Guidolin

Abstract

I review the burgeoning literature on applications of Markov regime switching models in empirical finance. In particular, distinct attention is devoted to the ability of Markov Switching models to fit the data, filter unknown regimes and states on the basis of the data, to allow a powerful tool to test hypothesesformulated in the light of financial theories, and to their forecasting performance with reference to both point and density predictions. The review covers papers concerning a multiplicity of sub-fields in financial economics, ranging from empirical analyses of stock returns, the term structure of default-free interest rates, the dynamics of exchange rates, as well as the joint process of stock and bond returns.

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Paper provided by IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University in its series Working Papers with number 415.

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Date of creation: 2011
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Handle: RePEc:igi:igierp:415

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Cited by:
  1. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2011. "Combination Schemes for Turning Point Predictions," Tinbergen Institute Discussion Papers, Tinbergen Institute 11-123/4, Tinbergen Institute.
  2. Fernando F. Ferreira & A. Christian Silva & Ju-Yi Yen, 2014. "Information ratio analysis of momentum strategies," Papers 1402.3030, arXiv.org, revised Jul 2014.

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