Multi-Factorized Semi-Covariance of Stock Markets and Gold Price

Yun Shi, Lin Yang, Mei Huang and Jun Steed Huang
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Yun Shi: School of Management, Bay Campus, Swansea University, Swansea SA1 8EN, UK
Lin Yang: Department of Mathematics, Shanghai University of Finance and Economics, Shanghai 200433, China
Mei Huang: Department of Management, University of Toronto, Toronto, ON, M1C 1A4, Canada
Jun Steed Huang: Department of Computer, Carleton University, Ottawa, ON, K1S 5B6, Canada

JRFM, 2021, vol. 14, issue 4, 1-11

Abstract: Complex models have received significant interest in recent years and are being increasingly used to explain the stochastic phenomenon with upward and downward fluctuation such as the stock market. Different from existing semi-variance methods in traditional integer dimension construction for two variables, this paper proposes a simplified multi-factorized fractional dimension derivation with the exact Excel tool algorithm involving the fractional center moment extension to covariance, which is a complex parameter average that is a multi-factorized extension to Pearson covariance. By examining the peaks and troughs of gold price averages, the proposed algorithm provides more insight into revealing underlying stock market trends to see who is the financial market leader during good economic times. The calculation results demonstrate that the complex covariance is able to distinguish subtle differences among stock market performances and gold prices for the same field that the two variable covariance may overlook. We take London, Tokyo, Shanghai, Toronto, and Nasdaq as the representative examples.

Keywords: fractional moment; stock exchange; complex covariance; semi-variance (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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