Jump Interdependencies: Stochastic linkages among international stock markets

This study investigates the volatily jump contagion among the Asian, European (Germany, UK, & France) and US markets. In particular, it examines the stochastic linkages among the international stock markets and analyzes the self and cross-excitation of jumps. The discontinuities in the stochastic volatility of each market are identified and their structural inter-dependencies are analyzed. Our empirical results imply that negative jumps from the USA and Europe are transmitted to the domestic Asian markets, while positive jumps are majorly from the regional markets. Results also imply that the cross-market linkages vary with respect to markets and regimes. Our results have implications for risk management, investment and hedging decisions.     

Multiscale financial risk contagion between international stock markets: Evidence from EMD-Copula-CoVaR analysis

Considering the frequency domain and nonlinear characteristics of financial risks, we measure the multiscale financial risk contagion by constructing EMD-Copula-CoVaR models. Using a sample composed of nine international stock markets from January 4, 1999, to May 13, 2021, the empirical study reveals that: (1) EMD-Copula-CoVaR models can effectively measure the multiscale financial risk contagion, and the financial risk contagion is significant at all time scales; (2) The high-frequency component is the major contributor of financial risk contagion; meanwhile, the low-frequency component is the smallest among all time scale components; (3) The risk export of the US financial market to other markets, except the UK under the original and medium-frequency component, is higher than that it receives; and (4) Even though the magnitude of overall financial risk contagion is similar for the COVID-19 pandemic, Subprime Crises, 9/11 terrorist attack and other crises, the relative importance of different frequency components is heterogeneous. Therefore, the countermeasures of risk contagion should be designed according to its multiscale characteristics.     

The asymmetric effect of crude oil prices on stock prices in major international financial markets

The aim of this paper is to explore the potential asymmetric impacts of positive and negative shocks in crude oil prices on stock prices in six major international financial markets which include China, Hong Kong, America, Japan, Britain, and Germany. We test for these asymmetric effects on 8 major international financial markets indices over the 2007M01–2020M03 periods. Our independent measures include the prices of Brent crude oil futures and West Texas Intermediate (WTI) futures. We use the nonlinear ARDL (NARDL) model proposed by Shin et al. (2014), which can capture both short- and long-run nonlinearities through positive and negative partial sum decompositions of the explanatory variables. This research finds that positive and negative fluctuations of oil price have asymmetric effects on stock price index in four financial markets, but the performance of the asymmetry is different. Specifically, the impacts of volatility in oil prices on two indices of Chinese stock prices are different, and the asymmetric effects of oil price volatility on stock price indices in China and other financial markets are significantly different.     

Measuring extreme risk spillovers across international stock markets: A quantile variance decomposition analysis

This paper proposes a quantile variance decomposition framework for measuring extreme risk spillover effects across international stock markets. The framework extends the spillover index approach suggested by Diebold and Yilmaz (2009) using a quantile regression analysis instead of the ordinary least squares estimation. Thus, the framework provides a new tool for further study into the extreme risk spillover effects. The model is applied to G7 and BRICS stock markets, from which new insights emerged as to the extreme risk spillovers across G7 and BRICS stock markets, and revealed how extreme risk spillover across developed and emerging stock markets. These findings have important implications for market regulators.     

An analysis of dependence between Central and Eastern European stock markets

We examine the dependence structure between four Central and Eastern European (CEE) stock markets (Czech Republic, Hungary, Poland and Romania) using static and dynamic copula functions with different forms of tail dependence. We find evidence of positive dependence between all CEE stock markets, although this dependence is stronger between the Hungarian, Czech and Polish markets than between these markets and the Romanian market. We also find evidence of symmetric tail dependence, although not for the Hungarian and Czech markets. The dependence is time-varying and intensified after the onset of the recent global financial crisis. These results confirm that CEE stock markets are gradually coupling, a fact that has risk management implications for policymakers and investors.     

Inflation, output, and stock prices: Evidence from two major emerging markets

Research in economics and finance documents a puzzling negative relationship between stock returns and inflation rates in markets of industrialized economies. The present study investigates this relationship for Korea and Mexico. We show that the negative relationship between the real stock returns and unexpected inflation persists after purging inflation of the effects of the real economic activity. Johansen and Juselius cointegration tests verify that the long-run equilibrium between stock prices and general price levels is weak. However, in both economies, stock prices and general price levels seem to show a strong long-run equilibrium with the real economic activity. This paper benefited from the constructive suggestions of an anonymous referee. The remaining errors are the authors’ responsibility. Financial support from the Dr. Robert B. Pamplin, Jr., School of Business Administration, University of Portland, is greatly appreciated.     

Exploring the international linkages of the euro area: a global VAR analysis

This paper presents a quarterly global model combining individual country vector error‐correcting models in which the domestic variables are related to the country‐specific foreign variables. The global VAR (GVAR) model is estimated for 26 countries, the euro area being treated as a single economy, over the period 1979–2003. It advances research in this area in a number of directions. In particular, it provides a theoretical framework where the GVAR is derived as an approximation to a global unobserved common factor model. Using average pair‐wise cross‐section error correlations, the GVAR approach is shown to be quite effective in dealing with the common factor interdependencies and international co‐movements of business cycles. It develops a sieve bootstrap procedure for simulation of the GVAR as a whole, which is then used in testing the structural stability of the parameters, and for establishing bootstrap confidence bounds for the impulse responses. Finally, in addition to generalized impulse responses, the current paper considers the use of the GVAR for ‘structural’ impulse response analysis with focus on external shocks for the euro area economy, particularly in response to shocks to the US. Copyright © 2007 John Wiley & Sons, Ltd.     

Monetary policy announcements and stock reactions: An international comparison

This article investigates the impact of domestic monetary policy rate announcements on the stock markets of New Zealand, Australia, the United Kingdom and the euro area, using event-study methods to identify stock price reactions to the unanticipated/surprise component of announcements. As Australia and New Zealand did not reach the zero bound we investigate whether there is an impact from the global financial crisis on stock market reactions that can be distinguished from the asymmetric reactions to surprises that characterise the business cycle. We find that the euro area and the UK both show a financial crisis effect but behaviour in New Zealand and Australia does not change. We conduct robustness checks and explore confounding factors, especially the impact of ‘guidance’ from central banks that prepares markets for policy rate changes.     

Non-linear causal linkages of EPU and gold with major cryptocurrencies during bull and bear markets

This paper sets out to explore whether the innovative Economic Policy Uncertainty (EPU) index and the safe haven asset of gold influence returns of high-capitalization cryptocurrencies in a non-linear manner. Estimations take place both concerning flourishing and stressed periods in the digital currency markets. Econometric outcomes reveal that the returns of almost half of the cryptocurrencies investigated are tightly connected to the EPU index in bull markets while even more currencies are linked with the index during bear markets. Similar findings are revealed as concerns gold as it proves to be more influential during bear markets due to its hedging capacities. There is also evidence that causality in variance is significant in all but the higher quantile concerning both EPU and gold estimations in both bull and bear markets.     

The impacts of investor sentiment on returns and conditional volatility of international stock markets

One of the main arguments of behavioral finance is that some properties of asset prices are most probably regarded as deviations from fundamental value and they are generated by the participation of traders who are not fully rational, thus called noise traders. Noise trader theory postulates that sentiment traders have greater impact during high-sentiment periods than during low-sentiment periods, and sentiment traders miscalculate the variance of returns undermining the mean-variance relation. The main objective of this research is to construct a model to evaluate the returns and conditional volatility of various stock market indexes considering the changes in the investor sentiment by measuring the effects of noise trader demand shocks on returns and volatility. EGARCH model is used to determine whether earning shocks have more influence on the conditional volatility in high sentiment periods weakening the mean–variance relation. This paper takes an international approach using weekly market index returns of U.S., Japan, Hong Kong, U.K., France, Germany, and Turkey. Weekly trading volumes of these indexes are regressed against a group of macroeconomic variables and the residuals are used as proxies for investor sentiment and significant evidence is found that there is asymmetric volatility in these market indexes and earning shocks have more influence on conditional volatility when the sentiment is high.     

Dynamic behaviors and contributing factors of volatility spillovers across G7 stock markets

This paper investigates the evolutions and determinants of volatility spillover dynamics in G7 stock markets in a time-frequency framework. We decompose volatility spillovers into short-, medium-, and long-term components, using a spectral representation of variance decompositions. The impacts of hypothesized factors on the decomposed volatility spillovers are also examined, using a linear regression model and fixed effects panel model. We find that the volatility spillovers across G7 stock markets are crisis-sensitive and are, in fact, closer to a memory-less process. The low-frequency components are the main contributors to the volatility spillovers; the high-frequency components are very sensitive to market event shocks. Moreover, our results reveal that the contributing factors have different effects on short-, medium-, and long-term volatility spillovers. There is no systematic pattern of the impacts of the contributing factors on volatility spillovers. However, whether the country is the transmitter or recipient of volatility spillovers could be a potential reason.     

Dependence structures between Chinese stock markets and the international financial market: Evidence from a wavelet-based quantile regression approach

In this study, we investigate the dependence structures between six Chinese stock markets and the international financial market including possible safe haven assets and global economic factors under different market conditions and investment horizons. The research is conducted by combining a quantile regression approach with a wavelet decomposition analysis. Although we find little or insignificant dependence under short investment horizons, we detect the strong asymmetric dependence of oil prices and the US dollar index on the six Chinese stock markets in the medium and long terms. Moreover, not only is crude oil not a safe haven, it may damage Chinese stock markets as it increases over the long term, even in bull markets. Meanwhile, appreciation of the US dollar (depreciation of RMB) damages (boosts) Chinese stock markets during bull (bear) market conditions under long investment horizons. Moreover, we find that VIX (volatility index)-related derivatives may serve as good risk management tools under any market condition, while gold is a safe haven asset only during crisis periods.     

Risk spillover analysis across worldwide ESG stock markets: New evidence from the frequency-domain

With the increasing global awareness of green environmental protection, the international environmental, social, and governance (ESG) stock markets are developing rapidly together with rising risk linkages across worldwide markets. Therefore, this study explores the risk spillover characteristics of international ESG stock markets in the time and frequency domains and constructs a risk linkage network to further explore the risk contagion mechanism. The results show that in most cases, the developed North American market is the core of outward risk spillover in international ESG stock markets. The entire system presents a small-world structure, and the internal regions display different risk spillover characteristics. Moreover, international ESG markets generally have strong time–frequency spillover and medium-frequency (a month to a year) spillover. In contrast, the high- (a day to a month) and low-frequency (more than one year) spillovers are located at relatively low levels, but they will rise significantly under sudden financial events. The empirical results expand the ESG stock market's theoretical framework and provide a reference for investors and market regulators to reduce the investment risk of ESG.     

The impact of COVID-19 on the G7 stock markets: A time-frequency analysis

We examine the co-movement of the G7 stock returns with the numbers of confirmed COVID-19 cases and causalities based on daily data from December 31, 2019 to November 13, 2020. We employ the wavelet coherence approach to measure the impact of the numbers of confirmed cases and deaths on the G7 stock markets. Our findings reveal that both the number of confirmed COVID-19 cases and the number of deaths exhibit strong coherence with the G7 equity markets, although we find heterogeneous results for the Canadian and Japanese equity markets, in which the numbers of COVID-19 cases and the deaths exhibit only a weak relationship. This evidence is more pronounced in the long-term horizon rather than the short-term horizon. Moreover, the lead-lag relationship entails a mix of lead-lag relations across different countries. We present the implications of these findings for both policymakers and the international investment community.     

The nexus between exchange rates and stock markets: evidence from the euro-dollar rate and composite European stock indices using rolling analysis

Both the goods market hypothesis and the portfolio balance theory, suggest a nexus between exchange rates and stock prices, albeit with a different direction of causality. This paper, using daily data, takes up the issue of the linkages between stock prices and exchange rates in the case of the euro-dollar rate and two composite European stock market indices: the FTSE Eurotop 300 and FTSE eTX All-Share Index. It addresses the causal ordering issue between the two markets using rolling unit root, cointegration and Granger causality tests. This methodological approach allows for the emergence of a clearer picture of the possible dynamic linkages between exchange rates and stock prices. The empirical results provide evidence of time-varying causality between the two markets.     

The Heisenberg picture in the analysis of stock markets and in other sociological contexts

We review some recent results concerning some toy models of stock markets. Our models are suggested by the discrete nature of the number of shares and of the cash which are exchanged in a real market, and by the existence of conserved quantities, like the total number of shares or some linear combination of the cash and the shares. This suggests to use the same tools used in quantum mechanics and, in particular, the Heisenberg picture to describe the time behavior of the portfolio of each trader. We finally propose the use of this same framework in other sociological contexts.     

Liquidity and asset pricing: Evidence from the Chinese stock markets

We introduce a novel two-factor model, incorporating market and liquidity factors, which outperforms the CAPM and Fama–French factor models when applied to stock market returns in Shanghai and Shenzhen over 2000–2019. We compute the liquidity factor as the return on a liquidity-mimicking portfolio, which we construct simultaneously using two measures of liquidity (one of them capturing liquidity’s trading-quantity dimension, and the other associated with its price-impact dimension). Unlike the CAPM and Fama–French factor models, the advocated two-factor model is able to account for numerous return anomalies, such as size, book-to-market ratio, earnings-to-price ratio, cash-flow-to-price ratio, return-on-equity, and volatility. The model’s performance is similar when applied separately to the Shanghai and Shenzhen stock markets. Furthermore, it fares similarly over the 1994–2004 and 2005–2019 sub-periods. This result is somewhat surprising, because liquidity seems likely to have been substantially lower over 1994–2004, as the Chinese markets were noticeably smaller, and the critical market reform aimed at eliminating non-tradable shares by the end of 2006 did not occur until 2005.     

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.     

Managerial bonding and stock liquidity: An analysis of dual-class firms

Given the decision to create a second class of stock through a dual-class structure, we propose that management is more (less) likely to create a liquid secondary market for both classes of shares the lower (higher) its willingness to tie its personal wealth to firm performance. If market makers recognize this relation, they should assign a higher likelihood to trades motivated by superior information in shares of firms that list both classes of stock and a lower likelihood for firms that list only one class of stock pursuant to recapitalization. Additionally, they should assign a lower likelihood to trades motivated by superior information in shares of IPOs that choose a dual-class structure and list only one class relative to IPOs that remain single-class. Our empirical tests based on IPOS and recaps between 1985 and 1988 provide support for these propositions.     

Dependent relationships between Chinese commodity markets and the international financial market: Evidence from quantile time-frequency analysis

In this article, the quantile time–frequency method is utilized to study the dependence of Chinese commodities on the international financial market. The impacts of risk management and diversification benefits of different portfolios are examined by calculating the reduction in downside risk. Moreover, we estimate and compare Sharpe Ratios (SRs) and Generalized Sharpe Ratios (GSRs) based on the frequencies of the investigated portfolios. Our empirical results reveal a strong asymmetric response from Chinese commodity markets. Specifically, we find that gold is a safe-haven asset, and due to negative correlations found at lower quantiles in medium and long term, an increase in the USD index damages bull commodity markets but boosts bear conditions under long-term investments, and negative (positive) tail correlations with interest rates (IRs) in bull (bear) markets are observed. It is proven that WTI can decrease short-run risks while USD and GOLD are more efficient in the diversification of downside risk. Adding international commodities may not improve the returns of Chinese commodities at given risk levels in the short and medium term through SRs and GSRs. In brief, investors should consider these dependence structures and modes of risk management in terms of time and frequency.