Reinforcement learning for option pricing and hedging, a practical edge over black-scholes-merton model
This thesis explores two frameworks leveraging on modern Reinforcement Learning (RL) techniques for pricing and dynamic hedging of an option under practical market conditions such as transaction costs, trader risk-aversion, and stochastic volatility which the Black-Scholes-Merton’s (BSM) model fails...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/175061 |