This study examines the application of AI frameworks in real-world scenarios, including regulatory compliance, fraud detection, credit scoring, default prediction, and portfolio management (Moscato et al., 2020). By leveraging AI to gain deeper insights into borrower creditworthiness, financial...

This study builds upon previous research by exploring the deeper relationship between the thematic and emotional content of top-charting music lyrics and stock price movements. Focusing on the Japan Nikkei Stock Average, this chapter investigate how thematic and emotional expressions in popular...

Accurately forecasting price swings is nowadays essential to investors looking to maximize their portfolios as the cryptocurrency markets continue to develop and fluctuate rapidly. The intricate, non-linear patterns in these markets are sometimes difficult for traditional financial models to...

This study compares the performance of two machine learning models - Long Short-Term Memory (LSTM) networks and XGBoost - in high-frequency intraday futures market forecasting. Using historical market data from five major Chinese futures markets, the research evaluates specialized classifiers in...

This paper investigates the volatility transmission between the S&P/TSX and key global financial markets, including the S&P500, Gold, VIX, WTI, and Brent Crude Oil (BO), using the Dynamic Correlation-Multivariate Stochastic Volatility (DC-MSV) model. By analyzing daily market index returns, the...

Natural Language Processing (NLP) has emerged as a transformative force in finance, enabling firms to extract insights from unstructured data sources such as news articles, earnings reports, and social media feeds. This chapter explores the integration of NLP techniques within the financial...

The integration of quantum machine learning (QML) into finance presents significant opportunities and challenges. QML offers immense computational power for analyzing large datasets and complex financial models, promising advancements in risk management, asset allocation, predictive modeling,...

Recent studies underscore the growing application of machine learning (ML) in finance, as revealed through bibliometric analyses. Kureljusic and Karger (2024) reviewed AI-based forecasting in financial accounting, identifying gaps and proposing future research agendas. Similarly, Biju et al....