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Forecasting Implied Volatility

Forecasting Implied Volatility. Alpha Asset Management Roger Kramer Brian Storey Matt Whalley Kristen Zolla. Objective and Methodology. Objective Develop a model that forecasts the CBOE Volatility Index (VIX) Methodology Sampling frequency – weekly Extensive variable development

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Forecasting Implied Volatility

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  1. Forecasting Implied Volatility Alpha Asset Management Roger Kramer Brian Storey Matt Whalley Kristen Zolla

  2. Objective and Methodology • Objective • Develop a model that forecasts the CBOE Volatility Index (VIX) • Methodology • Sampling frequency – weekly • Extensive variable development • Sample size – 313 observations • Two 50-week holdout samples

  3. Regression Model • Predictive Variables • VIX Level, Lag 1 • Intuition: Mean reversion • Negative correlation • Change in 10-Yr U.S. Treasury Yield, Lag 2 • Intuition: “Flight to quality” precedes equity market volatility • Negative correlation • Change in S&P 100 (if positive), Lag 1 • Intuition: Volatility affected by momentum effect of equity market • Positive correlation

  4. Final Model: Out-of-Sample Performance • First out-of-sample • 213-week sample; 50-week holdout for validation • Correct direction forecast: 64% • Second out-of-sample • 263-week sample; 50-week holdout for validation • Correct direction forecast: 60%

  5. Regression Analysis Summary Statistics

  6. Final Model Results • Trading Strategy #1 • Continuous trading – long or short every week • Correct direction forecast: 57.5% • VIX % Change > 0: 72.1% • VIX % Change < 0: 43.4% • Mean return (weekly): 3.89% • Mean return (winning weeks): 11.26% • Mean return (losing weeks): -6.14% • Standard deviation (weekly): 11.82% • Cumulative return (10/95 – 1/03): 2,300,000%

  7. Final Model Results • Trading Strategy #2 • Trade if absolute forecasted change in VIX exceeds 5% • Trade in 73 of 313 weeks (23.3% of the time) • Correct direction forecast: 63.0% • Mean return if trading (weekly): 5.95% • Mean return overall (weekly): 1.39% • Standard deviation (weekly): 5.73% • Cumulative return (10/95 – 1/03): only 4,591%

  8. Final Model Results

  9. Issues and Recommendations • VIX is Not Tradable • Develop an options trading strategy using VIX forecasts; i.e. buy/sell OEX straddles • Examine the effects of transactions costs • Naive Entry/Exit Signals • Double moving average crossovers • Various thresholds for forecasted VIX changes

  10. Conclusions • Our simple model predicts VIX direction with reasonable precision • With further research, similar model could be used for profitable trading

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