Signal Processing for Finance, Economics, and Marketing: Concepts, framework, and big data applications

Abstract

Economic data and financial markets are intriguing to researchers working on data and quantitative models. With rapid growth of and increasing access to data in digital form, finance, economics, and marketing data are poised to become one of the most important and tangible big data applications, owing not only to the relatively clean organization and structure of the data but also to clear application objectives and market demands. However, data-related economic studies often have different viewpoints from signal processing (SP). Also, many fundamental economics and business problems have been well formulated and studied in both theory and practice. The knowledge of foundational finance and economic theories will help SP and data researchers avoid reinventing the wheel and develop meaningful and useful research in these areas.

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