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Volatility in the stock market: ANN versus parametric models

  • S.I.: Recent Developments in Financial Modeling and Risk Management
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Abstract

Forecasting and adequately measuring equity returns volatility is crucial for portfolio selection and trading strategies. Implied volatility is often considered to be informationally superior to the realized volatility. When available, implied volatility is largely used by practitioners and investors to forecast future volatility. To this extent we want to identify the best approach to track equity returns implied volatility using parametric and ANN approaches. Using daily equity prices and stock market indices traded on major international Exchanges we estimate time varying volatility using the E-GARCH approach, the Heston model and a novel ANN framework to replicate the corresponding implied volatility. Overall the ANN approach results the most accurate to track the equity returns implied volatility.

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Notes

  1. Countless researches provide evidence of non stationarity in volatility of stock returns, just the cite few, Hsu (1984), Nelson (1991), Stărică and Granger (2005).

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Authors and Affiliations

  1. Sapienza University of Rome, Rome, Italy

    Rita Laura D’Ecclesia & Daniele Clementi

Authors
  1. Rita Laura D’Ecclesia
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  2. Daniele Clementi
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Correspondence to Rita Laura D’Ecclesia or Daniele Clementi.

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Appendix

Appendix

See Table 10.

Table 10 Heston Variance and E-GARCH conditional variances for Market Indices
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In Tables 11, 12, 13 and 14 the 350 stocks selected are shown.

Table 11 List of stocks chosen on the LSE
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Table 12 List of stocks chosen on the Tokyo Exchange
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Table 13 List of stocks chosen on the Australian Exchange
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Table 14 List of stocks chosen on the US Exchanges
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D’Ecclesia, R.L., Clementi, D. Volatility in the stock market: ANN versus parametric models. Ann Oper Res 299, 1101–1127 (2021). https://doi.org/10.1007/s10479-019-03374-0

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