New insights into the role of global factors in BRICS stock markets: A quantile cointegration approach

Because of the acceleration in marketization and globalization, stock markets in the BRICS (Brazil, Russia, India, China, and South Africa) countries are affected by various global factors, for example, oil prices, gold prices, global stock market volatility, global economic policy uncertainty, financial stress, and investor sentiment. This paper offers new insights into the short- and long-run linkages between global factors and BRICS stock markets by applying the quantile autoregressive distributed lags (QARDL) approach. This novel methodology enables us to test short- and long-run linkages accounting for distributional asymmetry. That is, the nonlinear dynamic relationship between the global factors and BRICS stock prices depends on market conditions. Our empirical results show that the effects of gold prices and global stock market volatility on BRICS stock prices are more significant in the long run than in the short run. A decrease in global stock market volatility is associated with higher stock prices, while gold prices demonstrate upward co-movement in dynamic correlations with stock markets. Irrational factors, such as economic policy uncertainty, financial stress, and investor sentiment, play a critical role in the short term, and negative interdependence is dominant. Finally, the rolling-window estimation technique is used to examine time-varying patterns between major global factors and BRICS stock markets.     

Market integration between conventional and Islamic stock prices

The paper assesses the market integration between conventional and Islamic stock prices from the long- and short-run perspectives for France, Indonesia, the UK and the US from September 8, 2008 to September 6, 2013 using various econometric approaches. The results show long-run relationships for all countries, except for the UK where there is no cointegration between conventional and Islamic stock prices. These findings suggest that the Islamic finance industry in the considered economies (except the UK) does not seem to be compliant to Islamic law's maxims, which hinders portfolio managers and market participants to benefit from the opportunities of international diversification and hedging effectiveness. From the correlation perspective, there is evidence of weak linkages between the Indonesian market and the developed markets for both conventional and Islamic stock prices, thus suggesting that investors can diversify their portfolios at the international level to minimize risk. However, there is high connection between the developed markets for both conventional and Islamic indexes. In addition, for each economy, the Islamic index is found to be strongly linked with its conventional counterpart. The structural change analysis reveals common break dates for several cross correlations, thus reflecting the similar time-paths of the interactions between markets. The presence of breaks in the inter-market linkages has important implications for international investors as regards portfolio diversification benefits and for financial policy makers regarding contagion risks and market policies.     

The impact of China's stock market reforms on its international stock market linkages

This paper investigates how China's stock market reforms have affected the stock market linkages between China and Korea, Japan and the US respectively. We firstly use a 4 × 4 asymmetric GARCH-BEKK model and a series of likelihood ratio tests to uncover China's regional and global linkages between 1992 and 2010 and during three sub-periods representing the stages of the Chinese reforms. The results show that Chinese stock market is linked to these overseas markets and the reforms permit spillovers to these markets from China. The subsequent regression analyses of the time-varying conditional correlations, in the presence of growing economic integration, exchange rate risk and financial turbulence, further indicate that the interdependences between China and the regional markets increase due to the implementation of liberalisation policies. However, the correlation between China and the global market remains weak even though this correlation responds positively to the institutional reforms on China's stock market additionally.     

Are the stock and real estate markets integrated in China?

This paper examines the dynamic short-run and long-run co-movement between the real estate and stock markets in China by employing a continuous wavelet method. We use gross domestic product and M2 (broad money supply) as control variables to eliminate the common factors of the two markets and to identify the real nexus between them. The empirical results show that the co-movement between real estate and stock prices is weak in the short run, except during the financial crisis period. Since the stock market is highly volatile, while real estate prices are relatively stable, the two markets are less correlated in the short run. The results also show that real estate prices affect stock prices in the long run, which supports the existence of a credit-price effect in China. Real estate prices remained very high in most time periods. Enterprises and individuals can obtain funds from bank loans to invest in the stock market, thus raising stock prices. These findings indicate that the two markets are generally segmented in the short run but are integrated in the long run. The stabilization of the real estate market is critical for stability in the stock market, but not vice versa. Additionally, investments in the two markets may not provide a high level of risk dispersion in the long run in China.

     

Time-frequency effect of crude oil and exchange rates on stock markets in BRICS countries: Evidence from wavelet quantile regression analysis

This study examines the effects of oil prices and exchange rates on stock market returns in BRICS countries (Brazil, Russia, China, India and South Africa) from a time–frequency perspective over the period 2009–2020. We use wavelet decomposition series to develop a threshold rolling window quantile regression to detect time–frequency effects at various scales. The empirical results are as follows. First, our findings confirm that the effects of both crude oil prices and exchange rates on BRICS stock returns are asymmetric. Positive shocks of crude oil have a greater impact on a bull market, whereas negative shocks have a greater impact on a bear market. Second, there is a short-term enhancement effect of crude oil and exchange rate on BRICS stock markets. In addition, volatility in the macro financial environment also exacerbates the impacts of oil prices and exchange rates on the stock market, and these fluctuations are heterogeneous. Overall, these findings provide useful insights for international investors and policy makers.     

Conditional correlations and volatility spillovers between crude oil and stock index returns

This paper investigates the conditional correlations and volatility spillovers between the crude oil and financial markets, based on crude oil returns and stock index returns. Daily returns from 2 January 1998 to 4 November 2009 of the crude oil spot, forward and futures prices from the WTI and Brent markets, and the FTSE100, NYSE, Dow Jones and S&P500 stock index returns, are analysed using the CCC model of Bollerslev (1990), VARMA-GARCH model of Ling and McAleer (2003), VARMA-AGARCH model of McAleer, Hoti, and Chan (2008), and DCC model of Engle (2002). Based on the CCC model, the estimates of conditional correlations for returns across markets are very low, and some are not statistically significant, which means the conditional shocks are correlated only in the same market and not across markets. However, the DCC estimates of the conditional correlations are always significant. This result makes it clear that the assumption of constant conditional correlations is not supported empirically. Surprisingly, the empirical results from the VARMA-GARCH and VARMA-AGARCH models provide little evidence of volatility spillovers between the crude oil and financial markets. The evidence of asymmetric effects of negative and positive shocks of equal magnitude on the conditional variances suggests that VARMA-AGARCH is superior to VARMA-GARCH and CCC.     

Dynamic relations between oil and stock market returns: A multi-country study

We study the relation between the BRENT and seventeen stock market indexes of important oil-dependent economies. We focus on connectedness between these markets and characterize the dynamics of transmission and reception. We use LASSO methods to shrink, select, and estimate the high dimensional network linking these markets between August, 1999 and March, 2018. This methodological innovation allows the inclusion of a significantly larger number of markets in the network, providing finer results regarding connectedness in the oil-stock market nexus. We show that transmission runs mainly from stock markets to the BRENT. Connectedness varies considerably over time, reaching peaks during times of financial distress. Dynamic predictive causality tests show evidence of time-varying bidirectional causality. Causality from stock markets to the BRENT is detected mostly for the last part of the sample period. This finding indicates that the impact of stock market developments on oil markets is growing over time.     

Should the government directly intervene in stock market during a crisis?

Unlike foreign exchange markets where central banks frequently intervene, the governments strive not to intervene in the stock markets since intervention transmit negative signals and carry market-related side effects. The main reasons often cited in support of intervention are to bring price stability and to restore investors’ confidence. During the recent economic turmoil, opportunities for the governments to intervene in the stock markets were mainly exploited in emerging and developing countries. We study the outcome of the Russian government's intervention in its major stock market between September and October 2008. This intervention was intended to reverse the sudden and swift declining trend in traded security prices by altering the market's expectations. By using a combination of event study and a multivariate GARCH model, our findings does not support direct government intervention in the stock market during a crisis.     

Does the stock market really cause unemployment? A cross-country analysis

This study examines the relationship between the stock market and unemployment in 30 advanced and 11 developing and emerging countries. The results show that the unemployment rate and stock prices are cointegrated in all country groups; further, the causality between stock prices and unemployment appears in all country groups. Specifically, I found a particularly strong and one-way causal direction from stock prices to the unemployment rate in G7 countries. There is a strong bilateral causal relationship between stock prices and unemployment for other advanced countries. However, in the 11 developing and emerging countries, the causality test results indicate a strong Granger causality from unemployment to stock prices. The results for developing and emerging countries suggest that the unemployment rate can help forecast stock prices, but not vice versa. These findings complement existing studies and deliver useful implications for investors and policymakers, and suggest some new lines for future research.     

Oil prices,stock returns,and exchange rates: Empirical evidence from China and the United States

Employing the diagonal BEKK model as well as the dynamic impulse response functions, this study investigates the time-varying trilateral relationships among real oil prices, exchange rate changes, and stock market returns in China and the U.S. from February 1991 to December 2015. We highlight several key observations: (i) oil prices respond positively and significantly to aggregate demand shocks; (ii) positive oil supply shocks adversely and significantly affect the Chinese stock market; (iii) oil price shocks persistently and significantly impact the trade-weighted US dollar index negatively; (iv) the US and China stock markets correlate positively just as the dollar index and the exchange rate does; (v) a significant parallel inverse relation exists between the US stock market and the dollar and between the China stock market and the exchange rate; and (vi) the Chinese stock market is more volatile and responsive to aggregate demand and oil price shocks than the US stock market in recent years.     

Risk and return in the Tehran stock exchange

This paper analyzes market index returns in the Tehran stock exchange (TSE) within the context of three variants of the Capital Asset Pricing Model: the static international; the constant-parameter intertemporal; and a Markov-switching intertemporal CAPM, which allows for time-varying degree of integration with regional and international equity markets. We find that TSE returns are CAPM-efficient at monthly frequency with respect to several international market indices. Moreover, we find evidence in support of international integration of the TSE with respect to international markets. In addition, we conduct an extensive investigation for the direction of causality between TSE returns, international market index returns, and those in neighboring countries.     

Dynamic relationship between stock prices and exchange rates for G-7 countries

There are two major findings from our time-series estimations. First, we find that there is no long-run significant relationship between stock prices and exchange rates in the G-7 countries. This result interfaces with Bahmani-Oskooee and Sohrabian’s (1992) finding, but contrasts with the studies that suggest there be a significant relationship between these two financial variables. Our second finding is that the short-run significant relationship has only been found for one day in certain G-7 countries. For instance, currency depreciation often drags down stock returns in the German financial market, but it stimulates the Canadian and UK markets on the following day. However, an increase in stock price often causes currency depreciation the next day in Italy and Japan. In addition, we also find that the record of stock price and the value of the dollar cannot be depended on when predicting the future in the US, either in the short-run or long-run.     

Nonlinear causality testing with stepwise multivariate filtering: Evidence from stock and currency markets

We examine the spillovers of the US subprime crisis to Asian and European economies and in particular to what extent currency and stock markets have been affected by the crisis. Linear and nonlinear dependencies are detected after pairwise and system-wise causality analysis. A new stepwise multivariate filtering approach is implemented after controlling for conditional heteroskedasticity in the raw data and in VAR/VECM residuals using multivariate GARCH models. Significant nonlinear causal linkages persisted even after the application of GARCH-BEKK, CCC-GARCH and DCC-GARCH modelling. This indicates that volatility effects might partly induce nonlinear causality. Perhaps new short-term asset-pricing models could be developed to explain this stylized fact. These results might also have important implications for hedging, trading strategies and financial market regulation.     

Speculative behavior and the dynamics of interacting stock markets

We develop a simple agent-based financial market model in which heterogeneous speculators apply technical and fundamental analysis to trade in two different stock markets. Speculators׳ strategy/market selections are repeated at each time step and depend on predisposition effects, herding behavior and market circumstances. Simulations reveal that our model is able to explain a number of nontrivial statistical properties of and between international stock markets, including bubbles and crashes, fat-tailed return distributions, volatility clustering, persistent trading volume, coevolving stock prices and cross-correlated volatilities. Against this background, our model may be deemed to have been validated.     

Testing for linear and nonlinear granger causality in the stock price-volume relation: Korean evidence

In this paper, linear and nonlinear Granger causality tests are used to examine the dynamic relationship between daily Korean stock returns and trading volume. We find evidence of significant bidirectional linear and nonlinear causality between these two series. ARCH-ype models are used to examine whether the nonlinear causal relations can be explained by stock returns and volume serving as proxies for information flow in the stochastic process generating volume and stock returns respectively. After controlling for volatility persistent in both series and filtering for linear dependence, we find evidence of nonlinear bidirectional causality between stock returns and volume series. The finding of strong bidirectional stock price-volume causal relationships implies that knowledge of current trading volume improves the ability to forecast stock prices. This evidence is not supportive of the efficient market hypothesis. Another finding is that the nonlinear relationship is sensitive to institutional, organizational, and structural factors. The results of this study should be useful to regulators, practitioners and derivative market participants whose success precariously depends on the ability to forecast stock price movements.     

Impact of COVID-19 pandemic on stock markets: Conventional vs. Islamic indices using wavelet-based multi-timescales analysis

We empirically explore the effect of the COVID-19 pandemic on Islamic and conventional stock markets from a global perspective. We also explore the co-movement between Islamic and conventional stock markets. Two comparable pairs of conventional and Islamic stock indices – Dow Jones Index and FTSE Index are considered in this study. Employing Wavelet-based multi-timescales techniques on the daily data from 21st January to 27th November 2020, our findings indicate that the pandemic creates identical volatility in both stock markets. Our findings further suggest that both markets are strongly associated and tend to co-move highly during our sample period, rebutting the decoupling hypothesis of the Islamic stock market from the conventional market. However, the Shariah screening process fails to provide immunity to Islamic stock markets against financial crises. Our findings suggest that investors should be aware that Islamic stocks' conservative features do not present a superior investment alternative, especially in economic turmoil.     

The outbreak of COVID-19 and stock market liquidity: Evidence from emerging and developed equity markets

The outbreak of the novel corona virus has heightened concerns surrounding the adverse financial effects of the outbreak on stock market liquidity and economic policies. This paper contributes to the emerging strand of studies examining the adverse effects of the virus on varied aspect of global markets. The paper examines the causality and co-movements between COVID-19 and the aggregate stock market liquidity of China, Australia and the G7 countries (Canada, France, Italy, Japan, Germany, the UK and the US), using daily three liquidity proxies (Amihud, Spread and Traded Value) over the period December 2019 to July 2020. Our empirical analysis encompasses wavelet coherence and phase-differences as well as a linear Granger causality test. Linear causality test results suggest that a causal relationship exists between the number of cases of COVID 19 infections and stock market liquidity. To quantitatively examine the degree of causality between COVID-19 outbreak and stock market liquidity, we employ the continuous wavelet coherence approach with results revealing the unprecedented impact of COVID-19 on stock market liquidity during the low frequency bands for countries that were hard hit with the COVID-19 outbreak, i.e., Italy, Germany, France, the UK and the US. Further, evidence shows that there is a heterogeneous lead-lag nexus across scales for the entire period of the study.     

On the globalization of stock markets: An application of Vector Error Correction Model,Mutual Information and Singular Spectrum Analysis to the G7 countries

This paper analyzes stock market relationships among the G7 countries between 1973 and 2009 using three different approaches: (i) a linear approach based on cointegration, Vector Error Correction (VECM) and Granger Causality; (ii) a nonlinear approach based on Mutual Information and the Global Correlation Coefficient; and (iii) a nonlinear approach based on Singular Spectrum Analysis (SSA). While the cointegration tests are based on regression models and capture linearities in the data, Mutual Information and Singular Spectrum Analysis capture nonlinear relationships in a non-parametric way. The framework of this paper is based on the notion of market integration and uses stock market correlations and linkages both in price levels and returns. The main results show that significant co-movements occur among most of the G7 countries over the period analyzed and that Mutual Information and the Global Correlation Coefficient actually seem to provide more information about the market relationships than the Vector Error Correction Model and Granger Causality. However, unlike the latter, the direction of causality is difficult to distinguish in Mutual Information and the Global Correlation Coefficient. In this respect, the nonlinear Singular Spectrum Analysis technique displays several advantages, since it enabled us to capture nonlinear causality in both directions, while Granger Causality only captures causality in a linear way. The results also show that stock markets are closely linked both in terms of price levels and returns (as well as lagged returns) over the 36 years analyzed.     

Financial contagion vulnerability and resistance: A comparison of European stock markets

This paper investigates contagion to European stock markets associated with seven big financial shocks between 1997 and 2002. We apply methods using heteroscedasticity-adjusted correlation coefficients to discriminate between contagion, interdependence and breaks in stock markets relationships. The analysis focuses on a comparison between developed Western European markets and emerging stock markets in Central and Eastern Europe. We find modest evidence of significant instabilities in cross-market linkages after the crises. The Central and Eastern European stock markets are not more vulnerable to contagion than Western European markets.     

Risk spillovers and hedge strategies between global crude oil markets and stock markets: Do regime switching processes combining long memory and asymmetry matter?

This paper investigates risk spillovers and hedge strategies between global crude oil markets and stock markets. In the paper, we propose a multivariate long memory and asymmetry GARCH framework that integrates state-dependent regime switching in the mean process with multivariate long memory and asymmetry GARCH in the variance process. Our results first show that there are linear risk spillovers running from the US stock markets to the WTI oil market in the short term. However, the linear risk spillover effect running from the oil market to the US stock market can only exist in the long term. In addition, there is a bidirectional linear risk spillover effect between the European stock markets and the Brent oil market in the short and long terms. Furthermore, there is no linear risk spillover effect between the Dubai oil market and the Chinese stock market. Second, the nonlinear risk spillovers running from the WTI oil market to the US stock market can be found in the tranquil regime. Moreover, there is also a nonlinear risk spillover effect running from the European stock markets to the Brent oil market in the tranquil regime. In addition, the nonlinear risk spillover effect running from the Brent oil markets to the European stock market can be found in the crisis regime. Furthermore, there is bidirectional nonlinear Granger causality between the Dubai crude oil market and the Chinese stock market in the tranquil regime. Finally, dynamic hedge effectiveness shows that the regime switching process combined with long memory and asymmetry behavior seems to be a plausible and feasible way to conduct hedge strategies between the global crude oil markets and stock markets.