International nonlinear causality between stock markets

In this paper, we test for linear and nonlinear Granger causality between the French, German, Japanese, UK and US daily stock index returns from 1973 to 2003. We find a strong contemporaneous linear dependence between European countries and a directional linear dependence from the US towards the other markets. Besides, linear causality increases after 1987, a finding consistent with the expected effects of financial liberalization of the 1980s and the 1990s. Above all, we document the presence of bidirectional nonlinear causality between daily returns. To check for spurious nonlinear causality, we filter out heteroskedasticity using a FIGARCH model. The dramatic decrease in the number of significant nonlinear causality lags confirms that heteroskedasticity played a major part in the previous findings. We then check if a few structural breaks can explain the remaining nonlinear causality. We find that a large number of nonlinear relationships vanish when we control for structural breaks, whereas linear causality remains.     

Integration of emerging stock markets with global stock markets

Financial integration for emerging economies should be seen as a long-term objective. In this paper, we examine stock market integration among five selected emerging stock markets (Brazil, China, Mexico, Russia and Turkey) and developed markets of the US, UK and Germany. The bounds testing approach to cointegration and error-correction modeling are used on monthly data from January 2001 to December 2014 to determine the short-run and long-run relationship between emerging stock market returns and the returns of the developed stock markets. The results show evidence of the existence of short-run integration among stock markets in emerging countries and the developed markets. However, the long-run coefficients for stock market returns in all emerging countries show a significant relationship only with Germany stock market return. The empirical findings in this study have important implications for academicians, international investors, and policymakers in emerging markets.     

Relationship between gold and stock markets during the global financial crisis: Evidence from nonlinear causality tests

This paper investigates the nonlinear dynamic co-movements between gold returns, stock market returns and stock market volatility during the recent global financial crisis for the UK (FTSE 100), the US (S&P 500) and Japan (Nikkei 225). Initially, the bivariate dynamic relationships between i) gold returns and stock market returns and ii) gold returns and stock market volatility are tested; both of these relationships are further investigated in the multivariate nonlinear settings by including changes in the three-month LIBOR rates. In this paper correlation integrals based on the bivariate model show significant evidence of nonlinear feedback effect among the variables during the financial crisis period for all the countries understudy. Very limited evidence of significant feedback is found during the pre-crisis period. Results from the multivariate tests including changes in the LIBOR rates provide results similar to the bivariate results. These results imply that gold may not perform well as a safe haven during the financial crisis period due to the bidirectional interdependence between gold returns and, stock returns as well as stock market volatility. However, gold may be used as a hedge against stock market returns and volatility in stable financial conditions.     

Time-varying market integration and stock and bond return concordance in emerging markets

We investigate the extent to which emerging stock market integration affects the joint behavior of stock and bond returns using a two-stage semi-parametric approach. Using a sample of 18 emerging markets, we find an unambiguous and robust link between emerging stock market integration and stock–bond return decoupling. We explain this with a decline in the segmentation risk premia in equities modeled by De Jong and De Roon [De Jong, F., De Roon, F.A., 2005. Time-varying market integration and expected returns in emerging markets. Journal of Financial Economics 78, 583–613] that leads to increased demand for stocks and reduced or unchanged demand for bonds. Our findings deliver new insights into the financial liberalization and stock–bond comovement literatures.     

Contagion as a domino effect in global stock markets

This paper shows that stock market contagion occurs as a domino effect, where confined local crashes evolve into more widespread crashes. Using a novel framework based on ordered logit regressions we model the occurrence of local, regional and global crashes as a function of their past occurrences and financial variables. We find significant evidence that global crashes do not occur abruptly but are preceded by local and regional crashes. Besides this form of contagion, interdependence shows up by the effect of interest rates, bond returns and stock market volatility on crash probabilities. When it comes to forecasting global crashes, our model outperforms a binomial model for global crashes only.     

Time-shift asymmetric correlation analysis of global stock markets

The time-shift asymmetric correlation analysis method is introduced for stock exchanges with different but non-overlapping trading hours to analyze the degree of global integration between stock markets of different countries and their influence on each other. Next-day correlation (NDC) and same-day correlation (SDC) coefficients are introduced. Correlations between major U.S. and Asia-Pacific stock market indices are analyzed. Most NDCs are statistically significant while most SDCs are insignificant. NDCs grow over time and the U.S. stock market plays a pacemaking role for the Asia-Pacific region. The correlation coefficients can be used as a measure of the degree of globalization for the corresponding countries.     

An empirical analysis of herd behavior in global stock markets

This paper examines herding behavior in global markets. By applying daily data for 18 countries from May 25, 1988, through April 24, 2009, we find evidence of herding in advanced stock markets (except the US) and in Asian markets. No evidence of herding is found in Latin American markets. Evidence suggests that stock return dispersions in the US play a significant role in explaining the non-US market’s herding activity. With the exceptions of the US and Latin American markets, herding is present in both up and down markets, although herding asymmetry is more profound in Asian markets during rising markets. Evidence suggests that crisis triggers herding activity in the crisis country of origin and then produces a contagion effect, which spreads the crisis to neighboring countries. During crisis periods, we find supportive evidence for herding formation in the US and Latin American markets.     

Modelling return and conditional volatility exposures in global stock markets

This article empirically investigates the exposure of country-level conditional stock return volatilities to conditional global stock return volatility. It provides evidence that conditional stock market return volatilities have a contemporaneous association with global return volatilities. While all the countries included in the study exhibited a significant and positive relationship to global volatility, emerging market volatility exposures were considerably higher than developed market exposures. JEL Classification G12     

Local and global price memory of international stock markets

The prime focus of this paper is on the impact of the world’s leading markets (USA, Japan, Hong Kong, UK, France, Switzerland and Germany) on the returns of the small Nordic markets (Denmark, Finland, Norway and Sweden). The order and the degree of processing both ‘local’ and ‘global’ information are uncovered using a combination of cointegration analysis and structural VAR modeling utilizing daily index returns. The results indicate that the US price changes, conditioned on the same day changes on the other markets, have an impact on all other markets during the following day, including the US market itself. Price changes on the Asian–Pacific markets are completely absorbed in price changes in Europe and do not have any direct effect on US prices. Finally, a cointegration relationship between Sweden and Norway is found, which affects also Finland.     

Time-varying linkages between energy and stock markets: Dynamic spillovers and driving factors

Integration between international energy prices and stock market returns is critical for global economics and politics. In this study, we employ a TVP-VAR (time-varying parameter vector autoregression) connectedness decomposition approach to investigate the time-varying linkages between a diversified energy portfolio comprising oil, coal, natural gas, and stock returns in G7 countries and China. This approach allows us to show the dynamic spillovers and explore the driving factors underlying the dynamic patterns. We find that geopolitical risks, global economic policy uncertainties, and equity market volatility can influence cross-market spillovers. This study expounds the effect of energy financialization.     

The recovery of global stock markets indices after impacts due to pandemics

The COVID-19 brings back the debate about the impact of disease outbreaks in economies and financial markets. The error correction terms (ECT) and cointegration processing tools have been applied in studies for identifying possible transmission mechanisms between distinct time series. This paper adopts the vector error correction model (VECM) to investigate the dynamic coupling between the pandemics (e.g., the COVID-19, EBOLA, MERS and SARS) and the evolution of key stocks exchange indices (e.g., Dow-Jones, S&P 500, EuroStoxx, DAX, CAC, Nikkei, HSI, Kospi, S&P ASX, Nifty and Ibov). The results show that the shocks caused by the diseases significantly affected the markets. Nonetheless, except for the COVID-19, the stock exchange indices reveal a sustained and fast recovering when an identical length time window of 79 days is analyzed. In addition, our findings contribute to point a higher volatility for all financial indices during the COVID-19, a strong impact over the Ibov-Brazil and its poor recover when compared to the other indices.     

Links and interdependence of developed stock markets under global economic crisis conditions

The scope of this article is to determine whether global stock markets behave differently under conditions of economic crisis by studying the interdependence among the price indices of 10 markets, including Dow Jones (DJ), DAX and NIKKEI. The stock markets under examination are those of the USA, Belgium, France, Germany, Greece, Italy, The Netherlands, Spain, the United Kingdom and Japan. The sample includes the logarithmic daily closing prices from 1 January 2000 to 20 February 2009, with a total of approximately 2.385 observations analyzed. The empirical findings suggest that the recent deep crisis has increased dramatically their correlation, thus tightening the existing links. Causality also seems to be affected by the crisis, as DJ and DAX cease to exert a dominant influence on the other stock indices. However, in all the other periods, the findings of previous studies (suggesting that DJ and DAX seriously affect the other indices) were verified, independent of the prevailing bear or bull market conditions.     

Time-varying risk in the German stock market

This paper compares two specifications of the Capital Asset Pricing Model for a sample of German stocks. The specifications generate time-varying first and second moments by conditioning on past information. This explicit modelling of the time series behaviour of risk allows us to characterize the driving factors of variances and covariances of returns. In addition to a variety of diagnostic tests we evaluate the validity of the one-factor restriction in the CAPM. The main findings are that risk is time dependent and very variable and also that more than one factor is needed to fit the data set.     

Interconnected multilayer networks: Quantifying connectedness among global stock and foreign exchange markets

This paper proposes a novel interconnected multilayer network framework based on variance decomposition and block aggregation technique, which can be further served as a tool of linking and measuring cross-market and within-market contagion. We apply it to quantifying connectedness among global stock and foreign exchange (forex) markets, and demonstrate that measuring volatility spillovers of both stock and forex markets simultaneously could support a more comprehensive view for financial risk contagion. We find that (i) stock markets transmit the larger spillovers to forex markets, (ii) the French stock market is the largest risk transmitter in multilayer networks, while some Asian stock markets and most forex markets are net risk receivers, and (iii) interconnected multilayer networks could signal the financial instability during the global financial crisis and the COVID-19 crisis. Our work provides a new perspective and method for studying the cross-market risk contagion.     

Time-varying impacts of demand and supply oil shocks on correlations between crude oil prices and stock markets indices

This paper investigates the time-varying impacts of demand and supply oil shocks on correlations between changes in crude oil prices and stock markets returns. The findings, obtained by means of a DCC-GARCH from June 2006 to June 2016, indicate that demand shocks positively affected the correlations between crude oil prices and stock market returns from late 2007 to mid-2008, during the apex of the financial markets volatility; from early 2009 to mid-2013, during global economy recovery from the financial crisis; and after 2015, when uncertainties about the Chinese growth and the US economy upturning arose. The dynamic conditional correlation, obtained after the removal of demand shocks effects, presented an average value of 0.13 when all economy sectors were considered and of 0.03 when the energy sector returns were excluded from the stock index. These correlations, still positive on average, suggest that exogenous supply oil shocks had little impact on US mainly enterprises cash flows over the last 10 years. Exceptions are the periods from 2006 to financial crisis and from 2014 until April 2016, when significant and unpredicted changes in oil market happened, considerably affecting the value of the main US companies.     

Quality investing in Asian stock markets

We examine two quality investing strategies using gross profitability (GP) or FSCORE, respectively, over the period of 2000–2016 in Hong Kong, Japan, Korea, Singapore and Taiwan stock markets. We find that the high-quality stocks generally earn positive returns in these markets. Both FSCORE and GP are significantly positively associated with subsequent stock returns in the cross-sectional regressions. We also find that financial institutions as sophisticated investor concern about stock quality. The actively managed institutions buy significantly more high-quality stocks than low-quality stocks in each of five Asian markets. The trading pattern is not significant in passively managed institutions.     

Procyclical volatility in Chinese stock markets

Review of Quantitative Finance and Accounting - We investigate the macroeconomic determinants of stock market volatility in China using the two-component GARCH-MIDAS model of Engle et al....     

Transmission of movements in stock markets

The paper analyses the relationships between three stock markets: New York, Tokyo and Frankfurt. The non-simultaneity of the trading times in these three markets determines the results of cross-correlations and regressions with daily returns. To cope with this and other problems, an empirical model is proposed and estimated. This model allows the separation of the ability to influence and the sensitivity of the different markets, and New York is found to be the most influential market, with Tokyo the most sensitive.     

Return predictability in African stock markets

This paper models weekly index returns adjusted for thin trading as a nonlinear autoregressive process with conditional heteroscedasticity to investigate the weak-form pricing efficiency of 11 African stock markets. Specifically, the use of the EGARCH-M model allows us to capture how conditional volatility affects the pricing process without imposing undue restrictions on the parameters of the conditional variance equation. On the basis of such a robust model, we are able to reject the evidence in prior studies that the Nigerian stock market is weak-form efficient. On the other hand, we confirm extant results that the markets in Egypt, Kenya, and Zimbabwe are efficient while that of South Africa is not weak-form efficient. We also generate new results, which point to the efficiency of the stock markets in Mauritius and Morocco, while the markets in Botswana, Ghana, Ivory Coast, and Swaziland are not consistent with weak-form efficiency.