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Automated Options Trading Using Machine Learning

We summarize an experimental study on the viability of several call option trading strategies that rely on our earlier work with machine-learning-based detection and prediction of heightened volatility periods. The proposed trading strategies makes use of the connection between call options prices and volatility in the underlying.1,2 As part of these strategies, the trader would purchase call options as soon as a period of heightened volatility has been detected, and, alternatively, predicted. After that, the strategies suggest the ideal time to sell the previously purchased options contracts in order to maximize profit. The approach is evaluated with simulated option trading experiments, results of which show that the idea has some merit. Furthermore, the experiments provide an empirical basis for choosing the optimal strategy from among the strategies we considered.