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<p>A class of stochastic volatility models with Markov dependent errors is introduced to analyze financial time series. The second-order properties of the resulting sequence are discussed. The parameters are estimated using generalised method of moments and Markov chain Monte Carlo methods. Simulation studies and data analysis are provided to illustrate the applications.</p>

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Stochastic Volatility Models with Correlated Innovations

  • 期刊论文

  • 发表日期：

    2025年10月2日

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  • N Balakrishna,
  • Himanshu Pokhriyal

摘要

A class of stochastic volatility models with Markov dependent errors is introduced to analyze financial time series. The second-order properties of the resulting sequence are discussed. The parameters are estimated using generalised method of moments and Markov chain Monte Carlo methods. Simulation studies and data analysis are provided to illustrate the applications.