Forecasting Implied Volatility

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 SP 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 gt 0 72.1
• VIX Change lt 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