Abstract
This study compares the efficacy of Black–Scholes implied volatility (BSIV) with model-free implied volatility (MFIV) in providing volatility forecasts for 13 North American, European, and Asian stock market indexes: S&P 500 (United States), S&P/ASX 200 (Australia), S&P/TSX 60 (Canada), AEX (the Netherlands), EURO STOXX 50 (Eurozone) CAC 40 (France), DAX 30 (Germany), HSI (Hong Kong), NIFTY 50 (India), Nikkei 225 (Japan), KOSPI 200 (Korea), SMI (Switzerland), and FTSE 100 (United Kingdom). In-sample volatility forecasts show that both BSIV and MFIV significantly improve the fit of a GJR-GARCH(1,1) model. However, BSIV dominates MFIV for predicting future volatility. Out-of-sample one-month volatility forecasts also indicate that BSIV outperforms both MFIV and GJR-GARCH(1,1) volatility.
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