3 papers
cs.LG2025
Dynamical errors in machine learning forecasts
Zhou Fang, Gianmarco Mengaldo
In machine learning forecasting, standard error metrics such as mean absolute error (MAE) and mean squared error (MSE) quantify discrepancies between predictions and target values.…
q-fin.TR2025
Option Market Making via Reinforcement Learning
Zhou Fang, Haiqing Xu
Market making of options with different maturities and strikes is a challenging problem due to its highly dimensional nature. In this paper, we propose a novel approach that combin…
q-fin.MF2025
Wasserstein Robust Market Making via Entropy Regularization
Zhou Fang, Arie Israel
In this paper, we introduce a robust market making framework based on Wasserstein distance, utilizing a stochastic policy approach enhanced by entropy regularization. We demonstrat…