A Wavelet Perspective of Crisis Contagion between Advanced Economies and the BRIC Markets

Abstract

This paper investigates the relationship between the BRICs’ and the advanced economies’ stock markets from 2000 to 2016 utilizing continuous wavelet transform. The continuous wavelet transform allows us to explore these relationships in the time–frequency domain to capture short- and long-term investors’ perspectives. Bi-directional spillovers are captured in terms of returns and volatility. In addition to covering the periods of the dot.com crash, the 11 September 2001 events, the pre-2007 financialization bubble period and the resulting Global Financial Crisis, we study volatility spillovers arising from the BRIC, U.S. and European market shocks post the Global Financial Crisis. Based on our results, we confirm findings in relatively fragmented literature that document time-varying and imperfect BRIC markets’ integration with mature economies. Overall, we show that arbitrage opportunities continue to exist in international stock market portfolios with respect to BRIC assets. In a major addition to the literature, our study captures spillovers from the advanced economies’ shocks to BRIC markets, as well as contagion from BRIC markets’ shocks to advanced economies’ markets.

Spillovers and contagion between BRIC and G7 markets: New evidence from time-frequency analysis

“…This has seen studies comparing the top developed and emerging markets. Notable works include [ 10 , 27 , 28 , 39 – 41 ]. In a static spillover paradigm, Zhang et al [ 27 ] analyse the connectedness of G7 and BRIC economies.…”

“…This influences other studies which consider the US and/or other developed markets in examining their diversification prospects with the BRIC economies. Gurdgiev and O’Riordan [ 10 ] employ the wavelet methodology to assess contagion between the US and BRIC markets with data from 2000 to 2016. Their findings corroborate those in sparse literature that describe the time-varying and uneven integration of BRIC markets with advanced economies.…”

“…Regarding the methods, the extant literature has been predominant with dynamic equicorrelation-fractionally integrated exponential GARCH [ 4 ], exponential GARCH [ 2 ], VAR-BEKK [ 54 ], dynamic equicorrelation GARCH [ 55 ], wavelets [ 10 ], BEKK-GARCH [ 56 ], DY-12 spillover index [ 21 , 29 , 51 ]; directed acyclic graph-SVAR [ 27 ]. These approaches, e.g., the GARCH techniques, VAR, and wavelets, could at best only determine spillovers and contagion, but cannot assess their magnitude and source(s).…”

“…Conversely, Russia appears to have decoupled greatly from worldwide financial flows volatility and patterns, particularly after the sharp decline in US–Russia geopolitical ties began in 2011. While these insights are prevalent in media and political science research, they have yet to be thoroughly investigated in financial literature on volatility and risk spillovers [ 10 ].…”

External shocks’ effects on the co-movements of currency and stock returns in three Southern African Development Community states

“…Wavelet approaches application to financial economics and investment is gathering momentum, recent examples being Michis (2022), Gurdgiev and O'Riordan (2021), AlNemer, Hkiri, and Khan (2021), modelling the co-movements in financial markets. Using a wavelet-based estimator of the partial correlation coefficient, Michis (2022) investigated the relationship between stock-market returns.…”