Directional Returns for Gold and Silver: A Cluster Analysis Approach

Handbook of Recent Advances in Commodity and Financial Markets: Quantitative Methods, Springer, Forthcoming

17 Pages Posted: 11 Apr 2016

Date Written: December 10, 2015

Abstract

This paper considers the directional predictability of daily returns for both gold and silver. These two metals have had a long history behaving sometimes as complements and other times as substitutes. We use daily data from June of 2008 through February of 2015. The last two years were removed as a set for validation of the model and the remainder, almost 5 years, was used as training. A cluster analysis yields six important clusters. An evaluation of these clusters leads to the formation of three strategies for directional predictions — up or down — for both gold and silver returns. The results of this analysis suggest that each strategy has its own advantages: the first strategy suggests that gold returns can be predicted better than those of silver; the second strategy shows that predicting up for gold also means predicting down for silver and the final strategy confirms that predicting up for silver also validates predicting down for gold.

Keywords: Gold, Silver, Directional Forecasting, Cluster Analysis, Neural Networks

JEL Classification: C5, C18, G1

Suggested Citation

Malliaris, A. (Tassos) G. and Malliaris, Mary, Directional Returns for Gold and Silver: A Cluster Analysis Approach (December 10, 2015). Handbook of Recent Advances in Commodity and Financial Markets: Quantitative Methods, Springer, Forthcoming, Available at SSRN: https://ssrn.com/abstract=2760045

A. (Tassos) G. Malliaris (Contact Author)

Loyola University Chicago ( email )

16 E. Pearson Ave
Quinlan School of Business
Chicago, IL 60611
United States
312-915-6063 (Phone)

Mary Malliaris

Loyola University Chicago ( email )

16 East Pearson Street
Chicago, IL 60611
United States
312-915-7064 (Phone)

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