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Category Archives: GARCH
Forecasting Volatility in the S&P500 Index
Echoing the findings of parallel empirical research, this study points to the conclusion that historical realized volatility adds little to the explanatory power of implied volatility forecasts. However, one perplexing feature of implied volatility forecasts is their persistent upwards bias. As a result, forecasting models using highfrequency historical data may have an edge over implied volatility forecasts in predicting the direction of future realized volatility. The ability to time the market by correctly predicting its direction approximately 62% of the time appears to offer the potential to generate abnormal returns by a simple strategy of buying and selling atthemoney straddles and deltahedging the resulting positions on a daily basis through to expiration, even after allowing for realistic transaction and hedging costs. Continue reading →
Posted in Derivatives, Forecasting, GARCH, Market Efficiency, Options, Volatility Modeling, volatility sign prediction forecasting Engle

Tagged ARFIMA, Direction Prediction, GARCH, Kurtosis, Long Memory, Market Efficiency, Option Pricing, Volatility, Volatility Risk

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