Stock Market Bubbles and the Forecastability of Gold Returns (and Volatility)

David Gabauer, Rangan Gupta, Sayar Karmakar () and Joshua Nielsen ()
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Sayar Karmakar: Department of Statistics, University of Florida, 230 Newell Drive, Gainesville, FL, 32601, USA
Joshua Nielsen: Boulder Investment Technologies, LLC, 1942 Broadway Suite 314C, Boulder, CO, 80302, USA

No 202228, Working Papers from University of Pretoria, Department of Economics

Abstract: Firstly, we use the Multi-Scale LPPLS Confidence Indicator approach to detect both positive and negative bubbles at short-, medium- and long-term horizons for the stock markets of the G7 and the BRICS countries. We were able to detect major crashes and rallies in the 12 stock markets over the period of the 1st week of January, 1973 to the 2nd week of September, 2020. We also observed similar timing of strong (positive and negative) LPPLS indicator values across both G7 and BRICS countries, suggesting interconnectedness of the extreme movements in these stock markets. Secondly, we utilize these indicators to forecast gold returns and its volatility, using a method involving block means of residuals obtained from the popular LASSO routine, given that the number of covariates ranged between 42 to 72, and gold returns demonstrated a heavy upper tail. We found that, our bubbles indicators, particularly when both positive and negative bubbles are considered simultaneously, can accurately forecast gold returns at short- to medium-term, and also time-varying estimates of gold returns volatility to a lesser extent. Our results have important implications for the portfolio decisions of investors who seek a safe haven during boom-bust cycles of major global stock markets.

Keywords: Gold; Stock Markets; Bubbles; Forecasting; Returns; Volatility (search for similar items in EconPapers)
JEL-codes: C22 C53 G15 Q02 (search for similar items in EconPapers)
Pages: 32 pages
Date: 2022-06
New Economics Papers: this item is included in nep-dem, nep-fmk, nep-for, nep-his and nep-rmg
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