10 citations · 13 across the 3 of their papers we have counts for
4 papers
Robot See, Robot Do: Imitation Reward for Noisy Financial Environments
Sven Goluža, Tomislav Kovačević, Stjepan Begušić +1
The sequential nature of decision-making in financial asset trading aligns naturally with the reinforcement learning (RL) framework, making RL a common approach in this domain. How…
Block-diagonal idiosyncratic covariance estimation in high-dimensional factor models for financial time series
Lucija Žignić, Stjepan Begušić, Zvonko Kostanjčar
Estimation of high-dimensional covariance matrices in latent factor models is an important topic in many fields and especially in finance. Since the number of financial assets grow…
Deep reinforcement learning with positional context for intraday trading
Sven Goluža, Tomislav Kovačević, Tessa Bauman +1
Deep reinforcement learning (DRL) is a well-suited approach to financial decision-making, where an agent makes decisions based on its trading strategy developed from market observa…
Scaling properties of extreme price fluctuations in Bitcoin markets
Stjepan Begušić, Zvonko Kostanjčar, H. Eugene Stanley +1
Detection of power-law behavior and studies of scaling exponents uncover the characteristics of complexity in many real world phenomena. The complexity of financial markets has alw…