Modeling and Forecasting of Financial Markets

Dear Colleagues,

This Special Issue aims to present contemporary advances in the modeling and forecasting of financial markets, offering a platform for empirical research that enhances our understanding of market behavior, and improves decision-making in finance. As financial systems become more complex and data-rich, the need for robust forecasting tools and accurate models has never been more critical, especially for academics, policymakers, and practitioners alike.

The focus of this Special Issue lies in exploring innovative approaches for financial market analysis, including time-series econometrics, machine learning, artificial intelligence, and other quantitative methods. Emphasis will be placed on both traditional financial indicators and alternative data sources, covering diverse markets such as equities, fixed income, commodities, and foreign exchange.

The scope of this Special Issue includes topics such as volatility modeling, return predictability, market microstructure, risk forecasting, and algorithmic trading strategies. Interdisciplinary and data-driven contributions that provide novel insights or practical forecasting applications are particularly encouraged.

This Special Issue is situated within a well-established literature on financial econometrics and market predictability. However, it distinguishes itself by addressing recent methodological advancements and the growing role of big data, thus bridging classical theories with modern computational techniques.

Prof. Dr. Kentaro Iwatsubo
Guest Editor

Manuscript Submission Information

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