Volatility Trading Strategies with Derivatives

To sum up, we observed that there exist strategies that could work and help earning positive profits. However, volatility forecasts using Garch (1,1) were not as good as they were before, and implied volatility forecast using not only Garch (1,1), but a combination of Garch and historical volatility sometimes is better. Moreover, good forecast not often meant positive profit. We have analyzed set of trading strategies on 2 companies: Amazon and GE. According to the obtained results, Strategy 1 and Strategy 2 appeared to perform quite well comparing them to delta hedge and straddle strategies. One of the possible explanations is different volatility forecast used in Strategy 1 and Strategy 2, which was derived from implied variance system. While Garch (1,1) forecast predicts volatility quite well on both companies, Garch forecast for GE and profit/loss relation are better than for Amazon. That happens due to the GE being less volatile and thus more predictable, as there is less uncertainty. Finally, we observe that Strategy 1 and Strategy 2 could work very well and earn positive profit on some weeks, especially Strategy 1. GE example was perfect illustration of how good can both of these strategies be. Amazon case showed that Strategy 1can be imperfect and work on the one week and do not work on the other. The key moment is that there exist volatility trading strategies that could earn positive profits even using Garch (1,1) model for the forecasting of volatility or a forecast of implied volatility based on the mix of Garch and historical volatility.