I’ve been thinking about an interesting problem lately: Suppose I have a position in an exotic derivative. How can I automate the hedging process?
Traditionally, one build a pricing model and calculate sensitivities to the risk factors. Then one uses various products like stocks, bonds, futures, swaps etc. to hedge each risk factor. The algorithm would need to determine how to hedge at each discrete time point. I think this has been covered in many papers so far.
I’ve also heard of people using AI to hedge. So suppose we have a preferred share ETF for example. Then the question becomes: given a discrete set of products with their price history, how can one optimally hedge? We need to calculate the weights of the portfolio and minimize the tracking error of the hedging portfolio. This would result in the optimal hedge.
What else could I try? Can someone point me towards some papers in this area? I’ve been thinking about this and might want to pursue the idea for my thesis. Thanks!