7 citations · 7 across the 1 of their papers we have counts for
3 papers
Arbitrage-Free Implied Volatility Surface Generation with Variational Autoencoders
Brian Ning, Sebastian Jaimungal, Xiaorong Zhang +1
We propose a hybrid method for generating arbitrage-free implied volatility (IV) surfaces consistent with historical data by combining model-free Variational Autoencoders (VAEs) wi…
Deep Q-Learning for Nash Equilibria: Nash-DQN
Philippe Casgrain, Brian Ning, Sebastian Jaimungal
Model-free learning for multi-agent stochastic games is an active area of research. Existing reinforcement learning algorithms, however, are often restricted to zero-sum games, and…
Double Deep Q-Learning for Optimal Execution
Brian Ning, Franco Ho Ting Lin, Sebastian Jaimungal
Optimal trade execution is an important problem faced by essentially all traders. Much research into optimal execution uses stringent model assumptions and applies continuous time…