{
  "title": "Modeling Stochastic Volatility with Application to Stock Returns",
  "publication": "IMF Working Papers, June 1, 2003",
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  "summary": "A stochastic volatility model where volatility was driven solely by a latent variable called news was estimated for three stock indices. A Markov chain Monte Carlo algorithm was used for estimating Bayesian parameters and filtering volatilities.",
  "sections": [
    {
      "heading": "Model and Estimation",
      "content": "- A stochastic volatility model was specified where volatility was driven solely by a latent variable called \"news\".\n- The model was estimated for three stock indices.\n- A Markov chain Monte Carlo algorithm was used for:\n  - Estimating Bayesian parameters.\n  - Filtering volatilities."
    },
    {
      "heading": "Key Findings",
      "content": "- Volatility persistence being close to one was consistent with both volatility clustering and mean reversion.\n- Filtering results indicated highly volatile markets, reflecting frequent pertinent news.\n- Diagnostics showed no model failure, although specification improvements were always possible.\n- The model corroborated stylized findings in volatility modeling."
    },
    {
      "heading": "Policy and Market Implications",
      "content": "- Potential value for market participants in asset pricing and risk management.\n- Potential value for policymakers in the design of macroeconomic policies conducive to less volatile financial markets.\n\n---\n\n Content in this bundle\n\n- Modeling Stochastic Volatility with Application to Stck Returns - WP/03/125\n  - Modeling Stochastic Volatility with Application to Stck Returns - WP/03/125 (Markdown version){rel=\"alternate\" type=\"text/markdown\"}\n  - Modeling Stochastic Volatility with Application to Stck Returns - WP/03/125 (PDF){rel=\"external\" type=\"application/pdf\"}\n\n---\n\nSource: https://www.imf.org/en/publications/wp/issues/2016/12/30/modeling-stochastic-volatility-with-application-to-stock-returns-16599"
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    "[Markdown version](/en/publications/wp/issues/2016/12/30/modeling-stochastic-volatility-with-application-to-stock-returns-16599/index.md)",
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    "Authors: Noureddine Krichene",
    "Published: June 1, 2003",
    "Series: IMF Working Papers",
    "DOI: https://doi.org/10.5089/9781451854848.001",
    "A stochastic volatility model was specified where volatility was driven solely by a latent variable called \"news\".",
    "The model was estimated for three stock indices.",
    "A Markov chain Monte Carlo algorithm was used for:",
    "Volatility persistence being close to one was consistent with both volatility clustering and mean reversion.",
    "Filtering results indicated highly volatile markets, reflecting frequent pertinent news.",
    "Diagnostics showed no model failure, although specification improvements were always possible.",
    "The model corroborated stylized findings in volatility modeling.",
    "Potential value for market participants in asset pricing and risk management.",
    "Potential value for policymakers in the design of macroeconomic policies conducive to less volatile financial markets.",
    "**Modeling Stochastic Volatility with Application to Stck Returns - WP/03/125**"
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