Dynamic efficiency of stock markets and exchange rates

We use generalized Hurst exponents to investigate long-range dependence across countries that have implemented an inflation targeting monetary policy regime and have a floating currency regime. We show that the degree of long-range dependence has changed after the 2008 crisis for equity markets but not as much for exchange rate markets. We compare results for developed and emerging economies and find that there still are some important differences but not as they were before the crisis. We also include an additional set of relevant countries and find that our results are more pronounced for inflation targeters. We discuss several implications of these results.     

Dynamic linkages between the center and periphery in international stock markets

This paper examines the dynamic linkages between the equity market of US representing the center and emerging markets using the Granger-causality test. The findings show that causality runs from the S&P500 to the stock prices of the 15 emerging markets but not vice versa.     

Are the China-related stock markets segmented with both world and regional stock markets?

Implementing the Capital Asset Pricing Model framework, this study investigates the integration of three China-related stock markets, namely, the A-, B- and H-share markets, with both the Hong Kong stock market and the world market. An analysis of market segmentation versus integration using the Jorion and Schwartz model suggests that the A-share market was a segmented market during the period 1995–2004. However, evidence of a higher-level integration between the A- and B-share markets, and the A-share and Hong Kong stock markets is found in the sub-period tests. The hypothesis that the B- and H-share markets are becoming increasingly integrated with the world stock market is not supported.     

Intraday volatility in the stock index and stock index futures markets

We examine the intraday relationship between returns and returnsvolatility in the stock index and stock index futures markets.Our results indicate a strong intermarket dependence in thevolatility of the case and futures returns. Price innovationsthat originate in either the stock or futures markets can predictthe future volatility in the other market. We show that thisrelationship persists even during periods in which the dependencein the returns themselves appears to weaken. The findings arerobust to controlling for potential market frictions such asasynchronous trading in the stock index. Our results have implicationsfor understanding the pattern of information flows between thetwo markets.     

Dynamic spillovers between energy and stock markets and their implications in the context of COVID-19

This study combined time-varying parameter vector autoregression (TVP-VAR) and a spillover index model to analyze the static, total, and net spillover effects of energy and stock markets before and after the COVID-19 outbreak. A network method was also used to depict structural changes more intuitively. Furthermore, we calculated and compared changes in the hedge ratio, optimal portfolio weights, and hedge effectiveness to guide investors to adjust portfolio strategies during COVID-19. The main findings were as follows: First, COVID-19 had a significant impact on spillover effects, and the average value of total spillover index increased by 19.94% compared with that before the epidemic. Second, the energy market was an important risk recipient of the stock market before COVID-19, and the extent of risk acceptance increased after the COVID-19 outbreak. Third, the hedging ratio, optimal portfolio weights, and hedge effectiveness showed huge changes after the COVID-19 outbreak, requiring investors to adjust their portfolio strategies.     

Dynamic volatility spillovers and investment strategies between the Chinese stock market and commodity markets

Building on the increased interest in the volatility spillover effects between Chinese stock market and commodity markets, this paper investigates the dynamic volatility spillovers of Chinese stock market and Chinese commodity markets based on the volatility spillover index under the framework of TVP-VAR. The result shows that there is a highly dependent relationship between the stock market and commodity markets. On average, the Chinese stock market is the net recipient of spillover, non-ferrous metals and chemical industry have a very obvious spillover impact on the stock market. The degree of total volatility spillover is different in different periods. After major crisis events, the volatility correlation between markets increases. Since the outbreak of COVID-19, the spillover effect of the stock market on the commodity market has been significantly enhanced. Then optimal portfolio weights and hedge ratios are calculated for portfolio diversification and risk management. The result shows that the ability of most commodities to hedge against risks is significantly reduced when the crisis occurs; NMFI (precious metals) and CRFI (grain) still have good hedging ability after the crisis, but the effectiveness of hedging risk is relatively low. Besides, the combination of CRFI and SHCI (the Shanghai composite index) is the most effective for risk reduction.     

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.     

Predicting returns in the stock and bond markets

Several predetermined variables that reflect levels of bond and stock prices appear to predict returns on common stocks of firms of various sizes, long-term bonds of various default risks, and default-free bonds of various maturities. The returns on small-firm stocks and low-grade bonds are more highly correlated in January than in the rest of the year with previous levels of asset prices, especially prices of small-firm stocks. Seasonality is found in several conditional risk measures, but such seasonality is unlikely to explain, and in some cases is opposite to, the seasonal found in mean returns.     

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.     

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.     

Dynamic and frequency-domain spillover among economic policy uncertainty,stock and housing markets in China

This study examines the dynamic characteristics of information spillover effect among economic policy uncertainty (EPU), stock and housing markets in China's first-, second- and third-tier cities. To measure return and volatility spillovers over time and across frequencies simultaneously, the researchers utilize the time-frequency connectedness network approach developed by Baruník and Křehlík (2018). The empirical findings suggest that return and volatility spillovers are stronger in the longer period (more than 3 months) than in the shorter period (1 to 3 months). In the short term, second and third-tier cities are net transmitters of information spillovers, while in the long term, first-tier cities, EPU, and stock markets are the net information transmitters. Furthermore, the long-term information from the EPU and stock market affect most of the real estate markets for different tier cities. Additionally, market segmentation reveals the city-specific characteristics of China's real estate market, especially the close connections between first-tier cities and the stock market. These results have important empirical implications for real estate policymakers and investors when they make related short or long-term decisions.     

Dynamic spillovers across oil,gold and stock markets in the presence of major public health emergencies

Extreme events have a systemic impact on global financial markets, leading to significant cross-market spillovers in the oil, gold, and stock markets and raising widespread concerns about market linkages and risk contagion. In this paper, with a focus on both return and volatility, a frontier spillover network analysis is used to examine the strength and scale characteristics of spillovers in the oil, gold and stock markets under major public health emergency shocks. In addition, the paper adopts a marginal spillover and network analysis to evaluate linkage relationships, risk sources and transmission paths in the oil, gold, and stock markets during such events. The results show that the return and volatility spillover effects generated across the oil, gold, and stock markets are significant, with return spillovers being more stable and volatility spillovers being highly sensitive to emergencies. Meanwhile, the COVID-19 pandemic has displayed the strongest return and volatility spillovers. The high intensity of the shocks during the COVID-19 period has changed the usual characteristics of the market, with the gold market becoming the risk receiver and the oil market becoming risk sources.     

Nonlinear interdependence of the Chinese stock markets

The methodologies and assumptions in financial integration studies are problematic and may lead to spurious empirical results. Using surrogate data analysis and the mutual prediction method of testing for nonlinear interdependence, it is feasible for an analyst, with a scant knowledge of the underlying dynamics of two dynamical systems, to show whether or not the systems are interdependent. This study applies these techniques in testing for nonlinear interdependence of three Chinese stock markets: Shanghai, Shenzhen, and Hong Kong. The empirical results of the present study indicate that the stock market series are nonlinear and that the Chinese stock exchanges are nonlinearly interdependent. Specifically, the evidence indicates that Shanghai and Shenzhen markets are bi-directionally interdependent, while Shanghai and Hong Kong as well as Shenzhen and Hong Kong markets are unidirectionally interdependent, with the direction of interdependence going from the mainland's markets to the Hong Kong market.     

The relationship between stock returns and volatility in international stock markets

This study examines the relationship between expected stock returns and volatility in the 12 largest international stock markets during January 1980 to December 2001. Consistent with most previous studies, we find a positive but insignificant relationship during the sample period for the majority of the markets based on parametric EGARCH-M models. However, using a flexible semiparametric specification of conditional variance, we find evidence of a significant negative relationship between expected returns and volatility in 6 out of the 12 markets. The results lend some support to the recent claim [Bekaert, G., Wu, G., 2000. Asymmetric volatility and risk in equity markets. Review of Financial Studies 13, 1–42; Whitelaw, R., 2000. Stock market risk and return: an empirical equilibrium approach. Review of Financial Studies 13, 521–547] that stock market returns are negatively correlated with stock market volatility.     

Persistence characteristics of the Chinese stock markets

Using advanced signal processing, this paper identifies the lack of ergodicity, stationarity, independence and the degree of persistence of the Shanghai (SHI) stock market and Shenzhen A shares (SZI) and B shares (SZBI), before and after the various deregulations and reregulations. Their lack of stationarity and ergodicity are ascribed to (1) the initial interventions in these stock markets by the Chinese government by imposing various daily price change limits, and (2) the changing trading styles, after the Chinese government left these equity markets to develop by themselves. The SHI, SZI, and SZBI are moderately persistent with Hurst exponents slightly greater than the Fickian 0.5 of the Geometric Brownian Motion. These stock markets were considerably more persistent before the deregulations, but they now behave more like Geometric Brownian Motions, i.e., efficiently. Thus, the Chinese stock markets are gradually and properly being integrated into one Chinese stock market. Our results are consistent with similar empirical findings from Latin American, European, and other Asian emerging financial markets.     

Oil shocks and stock markets: Dynamic connectedness under the prism of recent geopolitical and economic unrest

In this study we examine the dynamic structural relationship between oil price shocks and stock market returns or volatility for a sample of both net oil–exporting and net oil–importing countries between 1995:09 and 2013:07. We accomplish that, by extending the Diebold and Yilmaz (2014) dynamic connectedness measure using structural forecast error variance decomposition. The results for both stock market returns and volatility suggest that connectedness varies across different time periods, and that this time–varying character is aligned with certain developments that take place in the global economy. In particular, aggregate demand shocks appear to act as the main transmitters of shocks to stock markets during periods characterised by economic–driven events, while supply–side and oil–specific demand shocks during periods of geopolitical unrest. Furthermore, differences regarding the directions and the strength of connectedness can be reported both between and within the net oil–importing and net oil–exporting countries. These results are of particular importance to investors and portfolio managers, given the recent financialisation of the oil market.     

Dynamic linkages between emerging European and developed stock markets: Has the EMU any impact?

This paper investigates the short- and long-run behavior of major emerging Central European (Poland, Czech Republic, Hungary, Slovakia), and developed (Germany, US) stock markets and assesses the impact of the EMU on stock market linkages. Evidence of one cointegration vector in both a pre- and a post-EMU sub-period indicates market comovements towards a stationary long-run equilibrium path. Central European markets tend to display stronger linkages with their mature counterparts, whereas the US market holds a world leading influential role. No dramatic post-EMU shock is detected in stock market dynamics. The empirical findings have important implications for the effectiveness of domestic policy decisions, as the emerging Central European states have recently joined the EU and local stock markets may become less immunized to external shocks.     

Dynamic correlations and hedging effectiveness between gold and stock markets: Evidence for BRICS countries

This paper examines the dynamic relationships between gold and stock markets using data for the BRICS counties. For this purpose, we estimate the Asymmetric DCC model for weekly stock and gold data. Our main objective is to examine the time-varying correlations between the two assets and to check the effectiveness of gold as a hedge for equity markets. The empirical results reveal that the dynamic conditional correlations switch between positive and negative values over the period under study. These correlations are low to negative during the major financial crises suggesting that gold can act as a safe haven against extreme market movements. We also evaluate the implications for portfolio diversification and hedging effectiveness for the gold/stock pairs. Our findings suggest that adding gold to a stock portfolio enhances its risk-adjusted return.     

On jump processes in the foreign exchange and stock markets

This article investigates the existence of discontinuities inthe sample path of exchange rates and of a stock market index.Maximum-likelihood estimation of a mixed jump-diffusion processreveals that exchange rates exhibit systematic discontuinities,even after allowing for conditional heteroskedasticity in thediffusion process. The results are much more significant inthe foreign exchange market than in the stock market, whichsuggests differences in the structure of these markets. Finally,this jump component is shown to explain some of the empiricallyobserved mispricings in the currency options market.     

Liquidity and stock returns in pure order-driven markets: evidence from the Australian stock market

This paper examines the relationship between liquidity and stock returns in the pure order-driven stock market of Australia. The bid-ask spread, turnover rate, and amortized spread are used as proxies for liquidity. In addition to liquidity, other factors that have been found to influence stock returns, such as beta and size, are also considered. Seemingly unrelated regressions (SUR) and the cross-sectionally correlated timewise autoregressive (CSCTA) model form the methodological basis for this research. A small liquidity premium is found in the Australian market, which persists for the entire year. There is also strong evidence of a negative size effect.