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Volatility in the stock market: ANN versus parametric models

Rita Laura D’Ecclesia () and Daniele Clementi ()
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Rita Laura D’Ecclesia: Sapienza University of Rome
Daniele Clementi: Sapienza University of Rome

Annals of Operations Research, 2021, vol. 299, issue 1, No 44, 1127 pages

Abstract: 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.

Keywords: Conditional volatility; GARCH models; Heston model; ANN; Implied volatility; G14; C22 (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s10479-019-03374-0

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