Explaining co-movements between stock markets: The case of US and Germany

We explain co-movements between stock markets by explicitly considering the distinction between interdependence and contagion. We propose and implement a full-information approach on data for US and Germany to provide answers to the following questions:

(i) Is there long-term interdependence between US and German stock markets?

(ii) Is there short-term interdependence and contagion between US and German stock markets, i.e. do short-term fluctuations of the US share prices spill over to German share prices and is such co-movement unstable over high-volatility episodes?

Our answers are, respectively, no to the first question and yes to the second one.     

Risk,return, and liquidity during Ramadan: Evidence from Indonesian and Malaysian stock markets

Indonesia and Malaysia are common in religion; however, the two countries have different developments in their equity markets. This study investigates the risk, return, and liquidity during Ramadan for the Indonesia and Malaysia stock markets. We find that the volatility is higher around Ramadan for the Indonesia stock market, while displays dynamic patterns in different phases around the month of Ramadan for Malaysia. Despite the changing risk during Ramadan, the risk-adjusted return remains unchanged. Furthermore, this study finds that the liquidity in most stock index markets of the two countries is higher around Ramadan. These findings support the notion that Ramadan affects investors’ risk-taking attitude and facilitates the trade in stocks.     

Investigating volatility spillover of energy commodities in the context of the Chinese and European stock markets

This paper investigates spillover from energy commodities to Shanghai stock exchange and European Stock market, and identifies possible risks transmission and portfolio diversification opportunities. The study is conducted on daily spot prices of carbon (CO2) emission, natural gas and crude oil from 16 December 2010 to 29 December 2022, employing Granger causality test, dynamic conditional correlation (DCC), Diebold-Yilmaz (2012) and Barunik-Krehlic (2017) models. Results identify higher volatility and imply greater connectedness in the longer run. Additionally, natural gas is witnessed as the highest contributor of the shocks and crude oil as the highest receiver of the shocks from the network connection. Further results suggest for investment in energy commodities in shorter run rather than long run for efficient portfolio diversification. Results from this study are expected to have practical implications for portfolio managers, investors, and market regulators, given the suggestion of this study to incorporate energy stocks for efficient diversification of risk.     

Price behavior of small-cap stocks and momentum: A study using principal component momentum

This study analyzes why the negative momentum effect appears in Asian (China, Japan, Korea) stock markets, contrary to the U.S. market. We use principal component momentum (PMOM), a newly devised momentum measure. The PMOM is constructed by extracting commonalities from traditional momentum measures using principal component analysis. The results show evidence of positive and negative momentum profits in the U.S. and Asian markets, respectively. Negative momentum profits in Asian markets are attributable to the strong performance reversal of small stocks in the loser portfolio. Conversely, the positive momentum profits of the U.S. market are driven by the performance continuity of small stocks in the winner portfolio. The PMOM strategy is significantly more advantageous than traditional momentum strategies, based on the economic and statistical perspectives of momentum profits. These results are robust to changes in empirical designs.     

Does the US-China trade war affect co-movements between US and Chinese stock markets?

This paper investigates the impact of the US-China Trade War on co-movements between US and Chinese stock markets. It particularly examines the time-varying stock market co-movement between the United States and China at market level, as well as at sector level, over the period from 3rd January 2017 to 23rd January 2020. The ‘event study’ analysis is employed to investigate the effect of US-China trade disputes news on co-movement dynamics, and the news announcement effects before and after the official start of the US-China Trade War (regarded as 6th July 2018) are examined separately in light of this phenomenon. We also identify structural breaks and spillover patterns of cross-market co-movements during different phases. The results indicate that co-movements amongst mainland China, Hong Kong and US stock markets are positively affected by news releases and, after 6th July 2018, are enhanced significantly. More precisely, there is also empirical evidence of positive announcement effects in stock market co-movements between the US and mainland China in specific sectors (particularly, Industrials and Information Technology). For international investors, this evidence suggests that the US-China Trade War has reduced the benefit of portfolio diversification in managing risk.     

Trading volume and stock market volatility: The Polish case

Relying on the mixture of distributions hypothesis (MDH), this paper investigates the relationship between daily returns and trading volume for 20 Polish stocks. Our empirical results show that in the majority of cases volatility persistence tends to disappear when trading volume is included in the conditional variance equation, which is in agreement with the findings of studies on developed stock markets. However, we cannot confirm the testable implications of the MDH in all cases, which indicates that future research on the causes and modeling of Polish stock market volatility is necessary.     

Risk-based portfolio strategy in emerging stock markets: economic significance from Brazil,Russia, India and China

The purpose of this paper is to examine the conditional volatility and correlation predictability of four emerging stock markets, and address the issue whether investors could exploit this predictability to earn excess returns from the minimum variance portfolio of index component stocks. Inevitably, transaction cost affects the conclusive results. Nevertheless, economic gain exceeding a conservatively high transaction cost could be derived from a number of conditional volatility and correlation models. One dominant model, the shrinkage model, outperforms the market across the countries, cost structures and performance measures. We also document the superiority of averaging methodologies. However, semiparametric modelling falls in a grey area of profitability – sometimes attractive whilst sometimes not attractive.     

The empirical relationship between risk and return: evidence from the UK stock market

Previous studies reach no consensus on the relationship between risk and return using data from one market. We argue that the world market factor should not be ignored in assessing the risk-return relationship in a partially integrated market. Applying a bivariate generalized autoregressive conditional heteroscedasticity in mean (GARCH-M) model to the weekly stock index returns from the UK and the world market, we document a significant positive relationship between stock returns and the variance of returns in the UK stock market after controlling for the covariance of the UK and the world market return. In contrast, conventional univariate GARCH-M models typically fail to detect this relationship. Nonnested hypothesis tests supplemented with other commonly used model selection criteria unambiguously demonstrate that our bivariate GARCH-M model is more likely to be the true model for UK stock market returns than univariate GARCH-M models. Our results have implications for empirical assessments of the risk-return relationship, expected return estimation, and international diversification.     

On the volatility spillover between lslamic and conventional stock markets: A quantile regression analysis

This paper aims at analyzing the degree and structure of interdependencies in terms of volatility (transmission, contagion) between Islamic and conventional stock markets on calm periods and at times of financial fragility and crisis. We focused on the recent financial instability periods and used the Quantile Regression-based GARCH model. Main results lead to very interesting conclusions. First, it has been found that Islamic stock markets are not totally immune to the global financial crisis. Second, a very strong interdependence is sensed from the conventional to the Islamic stock markets, especially, from the conventional developed markets to the Islamic Emerging and Arab markets and to the Islamic developed markets. Finally, it has been proved that the interdependencies from conventional to Islamic markets are propagated between Islamic markets. Our findings suggest that the Islamic finance industry does not seem able to provide cushion against economic and financial shocks that affect conventional markets.     

Tick size and market quality: Simulations based on agent‐based artificial stock markets

This paper investigates the way that minimum tick size affects market quality based on an agent‐based artificial stock market. Our results indicate that stepwise and combination systems can promote market quality in certain aspects, compared with a uniform system. A minimal combination system performed the best to improve market quality. This is the first study to analyse tick size systems that remain at the theory stage and compare four types of system under the same experimental environment. The results suggests that a minimal combination system could be considered a new direction for market policy reform to improve market quality.     

The choice between rights and underwritten equity offerings: Evidence from Chinese stock markets

We study the choice and valuation effects of alternative flotation methods using a sample of Chinese firms that must meet the return on equity (ROE) thresholds set by the government to raise equity capital. The ROE requirement, although changed over time, seems to play an important role on the valuation and performance of seasoned equity offerings. The analysis of 219 rights and 75 underwritten offerings between 2000 and 2004 shows that Chinese firms that are not qualified for the flotation method with a higher ROE requirement suffer the most at announcement and experience significantly lower buy-and-hold abnormal returns than those that are qualified. Our results suggest that the freedom to choose their preferred flotation method may be valuable to firms that meet the higher ROE requirement. Finally, our probit models identify several determinants of the choice of flotation methods.     

What drives Markov regime-switching behavior of stock markets? The Swiss case

To optimally account for dynamic and nonlinear changes in the stock market return distribution we evaluate competing Markov regime-switching model setups for the Swiss stock market. We find that the stochastic movement is optimally tracked by time-varying first and second moments and including a memory effect. Besides the superior dynamic properties, this setup exhibits appealing economic interpretations.     

The impacts of climate policy uncertainty on stock markets: Comparison between China and the US

The interplay between climate policy uncertainty and stock market performance has emerged as a pressing research question in light of the challenges posed by climate change to financial markets. This paper measures China's daily and monthly climate policy uncertainty (CPU) from Jan 2000 to Mar 2022 based on Chinese news data for the first time. Then, the nonlinear and lag impacts of the US CPU and China's CPU on the return, volatility, correlation and tail dependence of China's and US stock markets are investigated and compared by adopting copula function and the distribution lag nonlinear model (DLNM). The data of stock markets includes the Shanghai Composite Index (SSCI) and NASDAQ from Jan 2000 to Mar 2022 from the Choice database, and the Shenzhen Composite Index (SCI) and S&P 500 are used for the robustness test. The empirical results indicate that (1) the growth trend of China’s CPU index is similar to that of the US. However, there are significant differences between the impacts of these two CPUs on stock markets. (2) For China, high CPU decreases current stock market return and increases volatility but decreases it in the future. It could also increase the upper tail dependence between China’s and the US stock markets’ volatilities in current period. (3) For the US, CPU decreases stock market return in the short term but increases it in the long term. High CPU increases volatility in short term, decreases volatility in 5 months and increases it again after 6 months. Both low and high CPU could increase the correlation between China's and US stock markets' volatilities.     

Country world betas: The link between the stock market beta and macroeconomic beta

We assess the connection between stock market linkages and macroeconomic linkages by using a world index model. Specifically, we test the association between the stock market beta (the sensitivity of country stock market index to world index) and macroeconomic betas (the sensitivity of national output and inflation to world output and inflation). Output betas account for about 20–26% of the cross-section of stock market betas. Controlling for previously-documented factors affecting stock market comovements: world output volatility is somewhat significant, while inflation betas, trade openness and world stock market volatility are insignificant in accounting for variation in stock market betas.     

On the stability of long-run relationships between emerging and US stock markets

While most studies have found no cointegration between emerging and US stock markets, some recent studies do find a long-run relationship exists between these markets. In view of these mixed findings, this study examines the stability of long-run relationships between a number of emerging stock markets and the US stock market using recursive cointegration analysis. The results show that no long-run relationship exists between emerging markets and the US market over most of the sample period throughout 1997. However, we do find clear evidence of cointegration in response to the recent global emerging market crisis in 1997–1998. We conclude that significant crisis events can change the degree of cointegration between international stock markets and, therefore, need to be taken into account in studies of long-run relationships between international stock markets.     

The cross-sectional relationship between stock returns and domestic and global factors in the Chinese A-share market

By using an extension of the Fama and MacBeth cross-sectional regression model, this analysis examines the relationship between stock returns and (i) a local beta, (ii) two global betas, and (iii) some firm-specific characteristics in the Chinese A-share market. The results of the analysis suggest that neither the conditional local beta nor the global betas has a significant relationship with stock returns in A-shares. Our findings indicate that firm factors, such as the book-to-market ratio and firm size, are important in explaining stock returns. However, the size effect is sensitive to the specification of the model. Finally, the results of sub-period tests indicate that the A-share market did not become increasingly integrated with either the world stock markets or the Hong Kong stock market over the period 1995–2002.

Impact of liquidity on stock returns: an empirical investigation of the Tunisian stock market

This paper investigates the return–liquidity relationship on one Middle East and North Africa frontier market, the Tunisian Stock Exchange (TSE). The findings provide evidence that there is a significant and positive premium for companies with high price impact and low trading frequency. However, Tunisian investors appreciate more low spread stocks. We show, also, a non-linear relation between potential delays of execution and stock returns. In addition, we find that Tunisian investors require a premium to compensate past cumulative illiquidity risk (high price impact, low turnover and high potential delay of execution) over the prior three to 12 months and to compensate past cumulative spread over 12 months. We point out also that these effects are seasonal.     

A common factor analysis for the US and the German stock markets during overlapping trading hours

We employ a bivariate common factor model to establish a permanent-transitory decomposition of two major stock indices (the Deutsche Aktienindex (DAX) for Germany and the Dow Jones Industrial Average (DJIA) for the United States). Using high-frequency data, we (1) identify a common trend shared by both indices, (2) find that the DJIA contributes up to 95% to the total innovation of the common factor, (3) show that both markets adjust within minutes to a system-wide shock, and (4) verify by hypothesis testing that the DJIA is the driving force in the transatlantic system of stock indices.     

Oil price shocks and the US stock market: A nonlinear approach

We study the response of US stock market returns to oil price shocks and to what extent it behaves asymmetrically over the different phases of the business cycle. For this purpose, we decompose the oil price changes into supply and demand shocks in the oil market and assess the state-dependent dynamics of structural shocks on US stock returns using a smooth transition vector autoregression model. When nonlinearity is considered, quantitatively very different asymmetric dynamics are observed. Our findings show that the responses of US stock returns to disaggregated shocks are asymmetric over the business cycle and that the impact of demand-driven shocks on US stock returns is stronger and more persistent, especially when economic activity is depressed. Furthermore, the contribution of shocks to expectation-driven precautionary demand in recessions accounts for a larger share of the variability of US stock market returns than that predicted by standard linear vector autoregressions.     

Transitions in the stock markets of the US,UK and Germany

In an analysis of the US, the UK and German stock market, we find a change in the behaviour based on the stocks’ beta values. In the years 1995–2006, trades of stocks with high beta and large volume were concentrated in the IT and technology sector, whereas in 2006–2012 those trades are dominated by stocks from the financial sector. We show that an agent-based model can reproduce such a transition. We further show that the initial impulse for the transition might stem from the increase of high-frequency trading at that time.