Forecasting Volatility of Commodity, Currency, and Stock Markets: Evidence from Markov Switching Multifractal Models

Ruipeng Liu, Mawuli Segnon, Oguzhan Cepni, Rangan Gupta

Research output: Working paperResearch

Abstract

This paper adopts a bivariate Markov switching multifractal (MSM) model to reexamine co-movement in stochastic volatility between commodity, foreign exchange (FX) and stock markets. After the 2007-2008 global financial crisis understanding volatility linkages and the correlation structure between these markets becomes very important for risk analysts, portfolio managers, traders, and governments. Using daily data on stock indices and FX rates from developed and emerging countries and a range of commodities such crude oil, natural gas, aluminum, copper, gold, silver, platinum, wheat, corn, soybean and soybean oil we find evidence of (re)correlation between commodity, FX and stock markets. The bivariate MSM model compares favorably to a bivariate DCC-GARCH and univariate MSM model, especially at short (1, 5 and 10 days) forecasting horizons. Furthermore, we discuss its implications for risk and portfolio management.
Original languageEnglish
Place of PublicationPretoria
PublisherUniversity of Pretoria
Number of pages33
Publication statusPublished - Dec 2023
SeriesWorking Paper Series / Department of Economics. University of Pretoria
Number2023-40

Keywords

  • Multifractal processes
  • Volatility co-movement
  • Commodity returns
  • Foreign exchange returns
  • Stock returns

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