Equal Risk Option Pricing with Deep Reinforcement Learning

Explore a 37-minute conference talk by Frédéric Godin from Concordia University on equal risk option pricing using deep reinforcement learning. Delve into hedging-based pricing, market setup, and self-financing portfolios. Examine the hedging optimization problem and equal risk pricing for convex risk measures. Learn about policy approximation through neural networks and the sensitivity of prices to risk measures. Investigate the impact of underlying dynamics on equal risk prices and compare them to traditional pricing approaches. Discover the use of options as hedging instruments and expected penalties as objective functions. Gain insights into the connection between equal risk pricing and illiquid asset pricing in the context of IFRS 17. Part of the "2022-2023 Quantitative Finance Seminar" series at the Fields Institute.

Intro
Motivation
Hedging-based pricing
Market setup
Self-financing portfolios
Hedging optimization problem
Equal risk price for convex risk measures
Computation of equal risk prices
Policy approximation through a neural network
Sensitivity of prices to the risk measure
Impact of underlying dynamics on equal risk prices
Benchmarking to traditional pricing approaches
Use of options for as hedging instruments
Expected penalties as objective functions
Equal risk pricing and illiquid asset pricing (IFRS 17)
Conclusion