Forecasting Volatility to Trade Options Relative to Implied Volatility
Summary
The response suggests comparing a volatility forecast from a non-normal GARCH model with the volatility implied by option prices. If the options appear inexpensive relative to the forecast, the proposed position is to buy calls and puts; if the implied volatility is above the forecast, the proposed position is to sell them. This frames an options strategy around the difference between expected future volatility and the market's implied estimate.
It also mentions using an at-the-money straddle when the trader wants exposure primarily to volatility and is less confident about the underlying's direction. The document gives no backtest, forecast horizon, model specification, entry or exit rules, or treatment of costs and risk. Its short answer is a conceptual example, not evidence that the approach is profitable.
Key ideas
- A non-normal GARCH model is proposed to forecast volatility for comparison with option implied volatility.
- The response suggests buying calls and puts when options seem cheap relative to the forecast.
- It suggests selling options when implied volatility exceeds the forecast.
- An at-the-money straddle is offered as a way to focus more on volatility than underlying direction.
- The document provides no performance evidence or detailed trading rules.
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Full text
# Examples of algorithmic trading strategies for options # Examples of algorithmic trading strategies for options Most textbook examples, and resources online, talk about algorithmic trading of stocks, futures, forex, etc. They cover techniques like cointegration trading, ARIMA analysis, and many other more exotic ways to trade these instruments. However, one thing I really never see is examples of doing this exactly same thing for options on, say, stocks. Obviously this will be a little more difficult due to the nature of options but it doesnt seem impossible. Some examples I can (roughly) think of are trying to calculate better values for IV and such, and find mispricings in options that way. But there has to be some strategies based completely on the underlying, using the techniques above (such as ARIMA). What kind of examples of algorithmic trading of options exist? ## Answer by Axel Haddar (score 0) https://quant.stackexchange.com/a/32195 One could use a non-normal GARCH model to forecast the unconditional volatility and compare it to the implied volatility. If you believe that the market prices of European call and put options are too low and you should buy them. If your forecast of implied is less than the current implied volatility, then the market prices of European call and put options are too high and you should sell them. Nonetheless, options depends on the volatility and the price of the underlying if you are not sure about the price of your stock let's say, one could trade ATM Straddle so you only trade the volatility Hope it helps
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