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Study mode:
on
1
Intro
2
Motivation
3
Hedging-based pricing
4
Market setup
5
Self-financing portfolios
6
Hedging optimization problem
7
Equal risk price for convex risk measures
8
Computation of equal risk prices
9
Policy approximation through a neural network
10
Sensitivity of prices to the risk measure
11
Impact of underlying dynamics on equal risk prices
12
Benchmarking to traditional pricing approaches
13
Use of options for as hedging instruments
14
Expected penalties as objective functions
15
Equal risk pricing and illiquid asset pricing (IFRS 17)
16
Conclusion
Description:
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.

Equal Risk Option Pricing with Deep Reinforcement Learning

Fields Institute
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