Portfolio optimization is always the priority of market researchers, large financial institutional
investors, Mutual Fund, and Pension funds managers. Due to high volatility in the stock …

Purpose This paper aims to analyze the role and performance of different artificial
intelligence (AI) algorithms in forecasting future movements in the main indices of the world's …

There are several automated stock trading programs using reinforcement learning, one of
which is an ensemble strategy. The main idea of the ensemble strategy is to train DRL …

In recent years, there has been growing interest in using deep learning methods to improve
the accuracy of stock price prediction, which has always been challenging due to the …

The combination of the processes of widespread digitalization and globalization of the world
economy has led to a significant expansion of the global information environment. The …

In the rapidly evolving domain of finance, quantitative stock selection strategies have gained
prominence, driven by the pursuit of maximizing returns while mitigating risks through …

Predicting the price and trends of financial instruments is a major challenge in the financial
industry, impacting investment decision-making efficiency for various stakeholders. Although …

This study aims to address the common issue of biased estimation errors in time series
modeling by analyzing the error in locating ideal hyperparameters and defining appropriate …

The idea of an intelligent machine has fascinated humans for centuries. But what is
intelligence? Some define it as the capacity for learning, reasoning, understanding or, from a …

Nowadays, academics and finance industries are being discussed highly in the domain of
stock market trading due to which the improvement in economic globalization. Connections …