Advances in Forecasting Financial and Macroeconomic Variables Using Econometric Methods

Special Issue Editors:
Professor Norman R. Swanson
Department of Economics, Rutgers University, USA

Dr. Mingmian Cheng
Department of Finance, Lingnan College, Sun Yat-sen University, Guangzhou, China


Given that our current output of data is estimated to be at least 2.5 quintillion bytes per day, it goes without saying that we now have more data than ever before, with which to construct predictions of economic variables ranging from stock market indicators to measures of economic activity. This in turn has spurred a tremendous amount of research activity in recent years concerned in the areas of model estimation, specification, and testing. For example, many fields, ranging from economics to neuroscience, have been making substantial advances in the area of big data analysis, with new methods being advocated for machine learning, variable selection, shrinkage, and dimension reduction. At the same time many new techniques have been proposed for model selection and testing. This special issue brings all of the latest advances in forecasting financial and macroeconomic variables together by acting as a repository for papers, both empirical and theoretical, that advance the frontier of prediction. In particular, the editors encourage authors carrying our research in all areas related to the estimation, selection, and accuracy assessment of prediction models in economics, econometrics, and statistics related fields to submit their research to this special issue.

Quantitative Finance and Economics (QFE) tries hard to provide high-quality research information on development of sustainable finance via quantitative methods. Due to the increasing popularity of this topic, world-wide interest in the work performed by researchers in this area is constantly expanding.

Instruction for Authors:
Submission due date: 31 October 2018

Hal Pedersen, Norman R. Swanson
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Victor J. Valcarcel
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Paul Adjei Kwakwa, Hamdiyah Alhassan, Solomon Aboagye
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Diego Ardila, Dorsa Sanadgol, Didier Sornette
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