Stock market trading has been a subject of interest to investors, academicians, and
researchers. Analysis of the inherent non-linear characteristics of stock market data is a …

Automated trading, which is also known as algorithmic trading, is a method of using a
predesigned computer program to submit a large number of trading orders to an exchange …

Distributed Energy Resources (DERs) are being integrated into the power market by
customers rather than large scale energy suppliers, thereby slowly transforming the …

Artificial intelligence remarkably facilitates quantitative investment. A latest intelligent search
algorithm, grey wolf optimizer, is well integrated with support vector regression machine to …

We present a high-throughput infrastructure for the automated calculation of molecular
properties with a focus on battery electrolytes. The infrastructure is largely open-source and …

In this paper we propose and validate a trading rule based on flag pattern recognition,
incorporating important innovations with respect to the previous research. Firstly, we …

Computational finance is an emerging application field of metaheuristic algorithms. In
particular, these optimisation methods are becoming the solving approach alternative when …

This study extends a recurrent reinforcement portfolio allocation and rebalancing
management system with complex portfolio constraints using particle swarm algorithms. In …

Stock trading strategies pose challenging applications of machine learning for significant
commercial yields in the finance industry, drawing the attention of both economists and …

Growing evidence is suggesting that postings on online stock forums affect stock prices, and
alter investment decisions in capital markets, either because the postings contain new …