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Inter-Market Sentiment Analysis Using Markov Switching Bayesian VAR Analysis

In: Regulation of Finance and Accounting

Author

Listed:
  • Saeed Ebrahimijam

    (Eastern Mediterranean University)

  • Cahit Adaoglu

    (Eastern Mediterranean University)

  • Korhan K. Gokmenoglu

    (HBV University)

Abstract

This study examines the nonlinear interdependency among the volatility indexes of gold, oil, and stock markets. The volatility indexes are used as proxies for market sentiment for the period from March 2010 to March 2017. The Markov switching Bayesian vector autoregressive (MS–BVAR) method is applied to measure the interdependency of the lags of these volatility indexes. The empirical results show three unidirectional causal relationships, lag dependencies, and positive impacts of the different market sentiments. There is always a moderate volatility period between every transition from recession to expansion of volatility situations which consistently last for 41 days; high-risk and low-risk periods last for one and three day(s), respectively. The greatest impact is from the first lag of the stock market volatility on the gold market volatility.

Suggested Citation

  • Saeed Ebrahimijam & Cahit Adaoglu & Korhan K. Gokmenoglu, 2022. "Inter-Market Sentiment Analysis Using Markov Switching Bayesian VAR Analysis," Springer Proceedings in Business and Economics, in: David Procházka (ed.), Regulation of Finance and Accounting, chapter 0, pages 73-84, Springer.
    • Handle: RePEc:spr:prbchp:978-3-030-99873-8_6
    DOI: 10.1007/978-3-030-99873-8_6
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