2 papers
math.OC2026
A Two-Timescale Primal-Dual Framework for Reinforcement Learning via Online Dual Variable Guidance
Axel Friedrich Wolter, Tobias Sutter
We study reinforcement learning by combining recent advances in regularized linear programming formulations with the classical theory of stochastic approximation. Motivated by the…
econ.EM2025
Efficient Sampling for Realized Variance Estimation in Time-Changed Diffusion Models
Timo Dimitriadis, Roxana Halbleib, Jeannine Polivka +3
This paper analyzes the benefits of sampling intraday returns in intrinsic time for the realized variance (RV) estimator. We theoretically show in finite samples that depending on…