We conduct an extensive empirical analysis to evaluate the performance of the recently
developed reinforcement learning algorithms by Jia and Zhou [11] in asset allocation tasks …

News-driven quantitative trading (NQT) has been popularly studied in recent years. Most
existing NQT methods are performed in a two-step paradigm, ie, first analyzing markets by a …

Financial markets are a source of non-stationary multidimensional time series which has
been drawing attention for decades. Each financial instrument has its specific changing-over …

Financial trading is about buying, holding, and selling securities in the hope of making a
profit. Automation is a trending area in the engineering domain that can help maximize the …

In Forex market, designing effective strategies are a critical role in investment. However, it is
a challenging task due to its inherent characteristics, which include high volatility, trend …

Recent advancement in reinforcement learning has enabled robust data-driven direct
optimization on the investor's objectives without estimating the stock movements as in the …

How to derive an investor's preference is vital for investment advisors and online lending
platforms for targeted marketing strategies, eg, market segmentation and financial product …

Automated Trading Systems are constantly increasing their impact on financial markets, but
learning from historical data, detecting interesting patterns and producing profitable …

Recent advances in the field of machine learning have yielded novel research perspectives
in behavioural economics and financial markets microstructure studies. In this paper we …

Portfolio Management is the process of overseeing a group of investments, referred to as a
portfolio, with the objective of achieving predetermined investment goals and objectives …