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Clarifying the Response of Gold Return to Financial Indicators: An Empirical Comparative Analysis Using Ordinary Least Squares, Robust and Quantile Regressions
Open AccessEditorial

Empirical Finance

Graduate School of Economics, Kobe University, 2-1, Rokkodai, Kobe 657-8501, Japan
J. Risk Financial Manag. 2020, 13(1), 6; https://doi.org/10.3390/jrfm13010006
Received: 25 December 2019 / Accepted: 26 December 2019 / Published: 2 January 2020
(This article belongs to the Special Issue Empirical Finance)
The research field related to finance has made great progress in recent years due to the development of information processing technology and the availability of large-scale data. This special issue is a collection of 16 articles on empirical finance and one book review. The content is six articles on machine learning, five articles based on traditional econometric analysis, and five articles on emerging markets. The large share of articles on the application of machine learning is in line with recent trends in finance research. This special issue provides a state-of-the-art overview of empirical finance from economic, financial, and technical points of view. View Full-Text
Keywords: machine learning; artificial intelligence; financial econometrics; emerging markets machine learning; artificial intelligence; financial econometrics; emerging markets
MDPI and ACS Style

Hamori, S. Empirical Finance. J. Risk Financial Manag. 2020, 13, 6.

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