Purpose Machine learning (ML), and deep learning in particular, is gaining traction across a
myriad of real-life applications. Portfolio management is no exception. This paper provides a …

Cryptocurrency markets experienced a significant increase in the popularity, which
motivated many financial traders to seek high profits in cryptocurrency trading. The …

Portfolio management (PM) is a popular financial process that concerns the occasional
reallocation of a particular quantity of capital into a portfolio of assets, with the main aim of …

Computational finance combines machine learning with financial needs to provide more
efficient solutions for investment analysis and automated trading. In previous studies …

This paper proposes a novel online learning algorithm, named weak aggregating specialist
algorithm (WASA), and presents its theoretical bound. This algorithm has a flexible feature …

High-frequency trading is an extraordinarily intricate financial task, which is normally treated
as a near real-time sequential decision problem. Compared with the traditional two-phase …

Abstract Machine learning algorithms have been widely used to establish online portfolio
selection strategies. Meta-algorithm, one of the machine learning algorithms, has the …

Deep reinforcement learning (DRL) has revolutionized quantitative finance by achieving
excellent performance without significant manual effort. Whereas we observe that the DRL …

This study presents a Reinforcement Learning (RL)-based portfolio management model
tailored for high-risk environments, addressing the limitations of traditional RL models and …

In recent years, existing studies have sought to enhance the effectiveness of portfolio
optimization by modeling asset relations. However, employing conventional graph neural …