Online learning represents a family of machine learning methods, where a learner attempts
to tackle some predictive (or any type of decision-making) task by learning from a sequence …

Financial portfolio management is the process of constant redistribution of a fund into
different financial products. This paper presents a financial-model-free Reinforcement …

Portfolio optimization can be roughly categorized as the mean-variance approach and the
exponential growth rate approach based on different theoretical foundations, trading logics …

Portfolio optimization concerns with periodically allocating the limited funds to invest in a
variety of potential assets in order to satisfy investors' appetites for risk and return goals …

Quantitative investment aims to maximize the return and minimize the risk in a sequential
trading period over a set of financial instruments. Recently, inspired by rapid development …

The growing popularity of quantitative trading in pursuit of a systematic and algorithmic
approach to investment has drawn considerable attention among traders and investment …

This paper presents an online portfolio selection algorithm based on pattern matching
principle where it makes a decision on the optimal portfolio in each period and updates the …

The financial markets, which involve over\$90 trillion market capitals, attract the attention of
innumerable profit-seeking investors globally. Recent explosion of reinforcement learning in …

Automated trading is one of the research areas that has benefited from the recent success of
deep reinforcement learning (DRL) in solving complex decision-making problems. Despite …

Mean-variance portfolio optimization models are sensitive to uncertainty in risk-return
estimates, which may result in poor out-of-sample performance. In particular, the estimates …