The conventional literature on financial forecasting is often criticized for spurious predictions from biased estimators, data snooping, and approaches with inferior statistical properties. Along with the finance industry, mainstream finance research has started using machine learning (ML) and artificial intelligence (AI) methods to improve financial modelling for forecasting. Since this line of research crosses many domains, understanding the relevant prior work in particular for exploring the future directions are important and challenging both for academics and practitioners in the field. This chapter provides a systematic review of big data research methods used in finance with a particular focus on financial predictability, identifies the usefulness of these approaches compared to traditional predictive methods, and provides direction for future research.
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Front Matter
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Back Matter
