The article below is part of the paper I co-authored for the Algorithmic trading class, I took at Duke University. The project entailed creating a trading algorithm based on identifying volatility arbitrage opportunities to trade share options with indices as the underlying.
To isolate the volatility arbitrage opportunities, the team explored using delta hedging. This resulted in high trading costs and as a result, was not implemented in our final strategy. As a risk management tool, we used stop losses which significantly increased total returns managed the maximum drawdown to less than 10%. For this strategy to be acceptable as an industry tool, further work will need to carried out to optimize use of delta hedging.
The code can be found in this repository, which can be used on Quantconnect using the LEAN engine. The full report including original formatting can be viewed and downloaded here.
