Multiple time-scales analysis of global stock markets spillovers effects in African stock markets

Abstract

This paper examines the spillovers in time and frequency from emerging (Brazil, Russia, India, China), developed (US, UK, France, Germany and Japan) stock markets and oil prices toward seven African stock markets. The spillovers are examined from 2005 to 2016, taking into account the recent financial crises and the recent oil prices fall. We combine the generalized Vector AutoRegressive (VAR) framework and the Maximum Overlap Discrete Wavelet Transform (MODWT) to obtain the spillovers at different time scales. The results show that the relationships between African stock markets, world stock markets and oil prices depend on time scales. African stock markets could be a way of capital diversification for global stock markets at scale 1 (2-4 weeks) and for investors active in the oil market at scale 2 (4-8 weeks).

Multi-scale Features of Interdependence Between Oil Prices and Stock Prices

“…Overall, DCC estimations show that the interdependence between oil prices and stock returns of studied countries exists at low, medium and high frequencies. Our results are strongly supported by earlier studies of Gupta and Modise ( 2013 ), Asaolu and Ilo ( 2012 ), and Gourène et al ( 2019 ).…”

“…This study is related to the literature, which applies a wavelet approach to model the information flows across financial markets. Gourène et al ( 2019 ) examine the time and frequency interdependence nexus between African stock markets and oil prices and provide evidence that African equity markets integrate with themselves and the outside relies on the time scales, the global financial markets state and the economic connections. Additionally, African stock markets have a strong relationship with crude oil prices in the short and medium term, but this nexus is relatively weak in the long run.…”

Multi-Horizon Dependence between Crude Oil and East Asian Stock Markets and Implications in Risk Management

“…For example, [27] investigated the impact of oil shocks and stock crashes on correlations between oil and stock markets by using MODWT to avoid the lack of translation-invariance of DWT. [29] examines the spillovers in time and frequency from global stock market and oil prices toward African stock markets. They also select the MODWT to obtain the stock and oil returns at different time scales since the MODWT allows to have the data in time series on each scale and to analyze them more easily (unlike the CWT that converts data into a two-dimensional field).…”

Optimization of Stock Portfolios Using Goal Programming Based on the Kalman-Filter Method

“…There have been many problem topics raised in capital market research with discussions in various scientific fields such as statistical journals, applied mathematics economics, estimation, banking, etc. Several studies that take the topic of the stock market are ranking of cement companies on the Tehran stock exchange [1], Value-at-Risk prediction on Karachi stocks using the Bayesian method [2], examining exchange rate responses to changes in stock prices in OECD countries [3], comparing the performance of OLS bias correction estimator with NASDAQ prediction [4], combining the Vector Auto-Regressive method and Wavelet transform (MODWT) to determine the effect of global stock market spillover on African stocks [5], analyzing the condition of the Russian stock market after the 1998 crisis [6], developing methodology to predict daily stocks by combining the three prediction models tested in Istanbul [7], evaluating two models to estimate the Value at Risk of the return of SROCOI shares in Iran [8], Optimization of portfolios using a polynomial objective programming model [9], the impact of a pandemic for stock prices [10] and estimation stock prices in Indonesia after the pandemic [11].…”