This study reviewed the artificial intelligence (AI) and machine learning (ML) literature in the
finance field. Using a bibliometric approach, we collected 348 articles published in 2011 …

Recently, the popularity of using the expressive power of quantum computing to solve
known, challenging problems has increased remarkably. This study aims to develop a clear …

Quantum computing is among the most promising emerging techniques to solve problems
that are computationally intractable on classical hardware. A large body of existing works …

Predicting equities market trends is one of the most challenging tasks for market participants.
This study aims to apply machine learning algorithms to aid in accurate Nifty 50 index trend …

Financial Reynolds number works as a proxy for volatility in stock markets. This piece of
work helps to identify the predictability and herd behavior embedded in the financial …

ABSTRACT The integration of Artificial Intelligence (AI) into the financial industry has
witnessed significant growth, transitioning from an academic concept to widespread …

Equity market forecasting is difficult due to the high explosive nature of stock data and its
impact on investor's stock investment and finance. The stock market serves as an indicator …

This article endeavors to investigate the application of machine learning in behavioral
economics and behavioral finance to represent a profile of studies conducted in this field. To …

The operating system is designed to manage the hardware and software resources of a
computer. With the development of quantum computing, the management of quantum …

Over the last decade, print and online publications have published a huge number of articles
with proposals for the introduction and use of neural networks in existing business and …