1 citations · 1 across the 7 of their papers we have counts for
7 papers
From Arbitrage Removal to Density Extraction: A Model-Free Framework for Short-Dated Options
Aaron Wizman, Gabriel Turinici, Gregory Merran
We study risk-neutral density extraction from short-dated option chains. As expiry approaches, option premia decline and bid--ask spreads can be large relative to prices, making mi…
Vanishing L2 regularization for the softmax Multi Armed Bandit
Stefana-Lucia Anita, Gabriel Turinici
Multi Armed Bandit (MAB) algorithms are a cornerstone of reinforcement learning and have been studied both theoretically and numerically. One of the most commonly used implementati…
Softmax gradient policy for variance minimization and risk-averse multi armed bandits
Gabriel Turinici
Algorithms for the Multi-Armed Bandit (MAB) problem play a central role in sequential decision-making and have been extensively explored both theoretically and numerically. While m…
The impact of recovery rate heterogeneity in achieving herd immunity
Gabriel Turinici
Herd immunity is a critical concept in epidemiology, describing a threshold at which a sufficient proportion of a population is immune, either through infection or vaccination, the…
Regime-Aware Time Weighting for Physics-Informed Neural Networks
Gabriel Turinici
We introduce a novel method to handle the time dimension when Physics-Informed Neural Networks (PINNs) are used to solve time-dependent differential equations; our proposal focuses…
Optimal time sampling in physics-informed neural networks
Gabriel Turinici
Physics-informed neural networks (PINN) is a extremely powerful paradigm used to solve equations encountered in scientific computing applications. An important part of the procedur…
High order universal portfolios
Gabriel Turinici
The Cover universal portfolio (UP from now on) has many interesting theoretical and numerical properties and was investigated for a long time. Building on it, we explore what happe…