Artificial intelligence is used in all spheres of life, providing utility in all fields. It is used in finance, too, for managing risks associated with complex investment products known as derivative contracts. However, due to high transaction costs and other limitations, continuous trading may not be feasible. As a result, investors frequently make discrete portfolio adjustments to balance replication errors and trading costs while considering their risk tolerance levels. Combining RL with deep Neural Networks (NNs) has demonstrated remarkable capabilities for finance.
Consequently, a research team from Switzerland and the U.S. studied the application of RL agents in hedging derivative contracts in a recent study published in The Journal of Finance and Data Science. They emphasized that the primary challenge lies in the scarcity of training data, so the researchers must rely on accurate market simulators. Yet, creating such simulators introduces financial engineering problems, requiring model selection and calibration and resembling traditional Monte Carlo methods.
This study is…
