4 papers
Myopic Optimality: why reinforcement learning portfolio management strategies lose money
Yuming Ma
Myopic optimization (MO) outperforms reinforcement learning (RL) in portfolio management: RL yields lower or negative returns, higher variance, larger costs, heavier CVaR, lower pr…
Deep Hedging to Manage Tail Risk
Yuming Ma
Extending Buehler et al.'s 2019 Deep Hedging paradigm, we innovatively employ deep neural networks to parameterize convex-risk minimization (CVaR/ES) for the portfolio tail-risk he…
A new architecture of high-order deep neural networks that learn martingales
Syoiti Ninomiya, Yuming Ma
A new deep-learning neural network architecture based on high-order weak approximation algorithms for stochastic differential equations (SDEs) is proposed. The architecture enables…
Realized Local Volatility Surface
Yuming Ma, Shintaro Sengoku, Kazuhide Nakata
For quantitative trading risk management purposes, we present a novel idea: the realized local volatility surface. Concisely, it stands for the conditional expected volatility when…