20 citations · 24 across the 6 of their papers we have counts for
9 papers
Dynamic tail risk forecasting: what do realized skewness and kurtosis add?
Giampiero Gallo, Ostap Okhrin, Giuseppe Storti
This paper compares the accuracy of tail risk forecasts with a focus on including realized skewness and kurtosis in "additive" and "multiplicative" models. Utilizing a panel of 960…
Enhanced method for reinforcement learning based dynamic obstacle avoidance by assessment of collision risk
Fabian Hart, Ostap Okhrin
In the field of autonomous robots, reinforcement learning (RL) is an increasingly used method to solve the task of dynamic obstacle avoidance for mobile robots, autonomous ships, a…
Vulnerability-CoVaR: Investigating the Crypto-market
Martin Waltz, Abhay Kumar Singh, Ostap Okhrin
This paper proposes an important extension to Conditional Value-at-Risk (CoVaR), the popular systemic risk measure, and investigates its properties on the cryptocurrency market. Th…
Formulation and validation of a car-following model based on deep reinforcement learning
Fabian Hart, Ostap Okhrin, Martin Treiber
We propose and validate a novel car following model based on deep reinforcement learning. Our model is trained to maximize externally given reward functions for the free and car-fo…
Outer power transformations of hierarchical Archimedean copulas: Construction, sampling and estimation
Jan Górecki, Marius Hofert, Ostap Okhrin
A large number of commonly used parametric Archimedean copula (AC) families are restricted to a single parameter, connected to a concordance measure such as Kendall's tau. This oft…
Infinitely Stochastic Micro Forecasting
Matúš Maciak, Ostap Okhrin, Michal Pešta
Forecasting costs is now a front burner in empirical economics. We propose an unconventional tool for stochastic prediction of future expenses based on the individual (micro) devel…