Impact of financial market uncertainty and macroeconomic factors on stock–bond correlation in emerging markets

This paper examines the impact of global financial market uncertainty and domestic macroeconomic factors on stock–bond correlation in emerging markets. In particular, by applying the wavelet analysis approach, we are able to examine stock–bond correlations over different time horizons in ten emerging markets. We find that stock–bond correlation patterns vary significantly between the time horizons. In particular, the correlation in short horizon changes the sign rapidly showing sustainable negative episodes while the correlation in long horizon stays positive most of the time. The most important factor influencing stock–bond correlation in short horizon is the monetary policy stance, while the factors with the greatest long-term impact are inflation and stock market uncertainty. Finally, global stock market uncertainty plays a more significant role than global bond market uncertainty in explaining stock–bond correlations in emerging markets.     

Informational linkage and price discovery between China's futures and spot markets: Evidence from the US–China trade dispute

This study examines the effects of the US–China trade dispute on the informational linkages and price discovery between China's futures and spot markets. Using the daily price data of four assets representing the real and financial sectors in China during 2016–2019, empirical findings suggest that the futures–spot correlations for the stock index, copper, and corn markets have increased significantly during the trade dispute. In contrast, sharp declines in the dynamic correlations between gold futures and spot markets, as gold is a safe haven asset, are observed during the event window. During uncertainty disturbance (i.e., the trade dispute), the futures–spot cointegrated relationships in the gold and corn markets are found to adjust more quickly and efficiently, whereas the correction speeds of the market deviations for the stock index and copper market are moderately slower. With the intensive integration of market expectations with uncertainty shocks, the economic shocks of trade disputes tend to remarkably improve the pricing efficiency of China's futures markets, except for the gold futures market. China's spot markets, however, seem to be more sensitive to the noise trades and information disturbances arising from the trade dispute.     

How do policy and information shocks impact co-movements of China’s T-bond and stock markets?

We investigate the impacts of policy and information shocks on the correlation of China’s T-bond and stock returns, using originally the asymmetric dynamic conditional correlation (DCC) model that allows for the coexistence of opposite-signed asymmetries. The co-movements of China’s capital markets react to large macroeconomic policy shocks as evidenced by structural breaks in the correlation following the drastic 2004 macroeconomic austerity. We show that the T-bond market and the bond–stock correlations bear more of the brunt of the macroeconomic contractions. We also find that the bond–stock correlations respond more strongly to joint negative than joint positive shocks, implying that investors tend to move both the T-bond and stock prices in the same direction when the two asset classes have been hit concurrently by bad news, but tend to shift funds from one asset class to the other when hit concurrently by good news. However, the stock–stock correlation is found to increase for joint positive shocks, indicating that investors tend to herd more for joint bullish than joint bearish stock markets in Shanghai and Shenzhen.     

Stock salience and the asymmetric market effect of consumer sentiment news

We document asymmetric announcement effects of consumer sentiment news on United States stock and stock futures markets. While a negative market effect occurs upon the release of bad sentiment news, there is no market reaction for the counterpart good news. This supports the “negativity effect” hypothesis. Notably, this effect seems most likely to occur in salient stocks, which is consistent with the availability heuristic.     

Dynamic spillovers between uncertainties and green bond markets in the US,Europe, and China: Evidence from the quantile VAR framework

This paper investigates the quantile connectedness between uncertainties and green bonds in the US, Europe, and China by using a quantile VAR model-based connectedness approach. The empirical findings suggest that the spillover effect under extreme market conditions is significantly higher than that under normal market conditions. We also show that stock market uncertainty (VIX) and oil market uncertainty (OVX) have a greater impact on green bonds, especially in extreme upward markets. In addition, the US is the dominant transmitter of spillovers in other green bond markets, while China is always the net receiver of spillovers. Further research, meanwhile, demonstrates that the connectedness between green bonds and uncertainties is time-varying and that the spillover effects at extreme upper and lower quantiles are asymmetric and heterogeneous, especially in the early days of the COVID-19 pandemic. These findings provide investors and policymakers with systematic insights into the risk resistance of different green bond markets.     

Reprint of: Stock salience and the asymmetric market effect of consumer sentiment news

We document asymmetric announcement effects of consumer sentiment news on United States stock and stock futures markets. While a negative market effect occurs upon the release of bad sentiment news, there is no market reaction for the counterpart good news. This supports the “negativity effect” hypothesis. Notably, this effect seems most likely to occur in salient stocks, which is consistent with the availability heuristic.     

The determinants of stock–bond return correlations

I study the options-implied market risks that affect US stock–bond correlations from 2007 to 2021. I discover that US stock and bond market uncertainty, stock market tail risk, and global credit-default risk are dominant contributors to changing stock–bond correlations during the global financial crisis (GFC) period. However, these market risks collectively contribute much less to time-varying correlations in the post-GFC period. Furthermore, stock–bond correlations rise in times of rising US and global bond market risks. Rising stock market uncertainty raises stock–bond correlations in the GFC period but lowers them in the post-GFC period. My results disentangle the risks of stock and bond markets and show that equity tail risk, bond market risk, and stock market uncertainty are dominant factors in changing stock–bond diversification benefits in periods of market turmoil.     

The Lead‐Lag Relationship Between Cash and Stock Index Futures in a New Market

This paper investigates the lead‐lag relationship in daily returns and volatilities between price movements of the FTSE/ATHEX‐20 and FTSE/ATHEX Mid‐40 stock index futures and the underlying cash indices in the relatively new futures market of Greece. Empirical results show that there is a bi‐directional relationship between cash and futures prices. However, futures lead the cash index returns, by responding more rapidly to economic events than stock prices. This speed is much higher in the more liquid FTSE/ATHEX‐20 market. Moreover, results indicate that futures volatilities spill information over to the corresponding cash market volatilities in both investigated futures markets, but volatilities in the cash markets have no effect on the volatilities of futures markets. Overall, it seems that new market information is disseminated faster in the futures market compared to the stock market. This implies that the futures markets can be used as price discovery vehicles, providing further evidence that derivatives markets contribute to completing and stabilising capital markets in Greece. A further finding of this study is that futures volume and disequilibrium effects between cash and futures prices are important variables in the explanation of volatilities in cash and futures markets.     

Stock–bond dependence and flight to/from quality

This paper investigates the stock–bond dependence structure using a dependence-switching copula model. The model allows stock–bond dependence to switch between positive dependence regimes (contagions or crashes of the two markets during downturns or booms in both markets during upturns) and negative dependence regimes (flight-to-quality from stock markets to bond markets or flight-from-quality from bond markets to stock markets). Using data from four developed markets including the US, Canada, Germany, and France for the period between January 1985 and August 2022, we find that the within-country stock–bond (extreme) dependence could be both positive and negative. In the positive dependence regimes, the stock–bond dependence is asymmetric with stronger left tail dependence than the right tail dependence, giving evidence of a higher likelihood of joint stock–bond market crashes or contagions during market downturns than the collective stock–bond market booms. Under the negative dependence regimes, we find both flight-from-quality and flight-to-quality, with flight-to-quality being more dominant in the North American markets while flight-from-quality is more prominent in the European markets. Further, the dependence switches between positive and negative regimes over time. Moreover, the dependence is mainly in the positive regimes before 2000 while mostly in the negative regimes after that, indicating contagions mostly before 2000 and flights afterwards. Further, the dependence switches between positive and negative regimes around financial crises and the COVID-19 pandemic. These results greatly enrich the findings in the existing literature on the co-movements of stock–bond markets and are important for risk management and asset pricing.     

Price Discovery Between Informationally Linked Markets During Different Trading Phases

The dynamic nature of the price information transfer when stock and futures markets switch between different price trading phases is examined. This is undertaken by decomposing Australian stock indexes and share price index futures contract data into bear- and bull-market phases and analyzing the change in the power of the bidirectional information feedback between the futures market and small, medium, and large stocks. Results support the hypothesis that the nature of the price-discovery process varies with the trading phase. In particular, during the bull phase small stocks show a marked increase in price exogeneity and futures prices contain relatively less price-sensitive fundamental information. We argue that in bull phases, futures trading becomes increasingly associated with noninformation trading such as realizing paper profits, portfolio rebalancing, and increased noise trading.     

An alternative approach to evaluating the agreement between financial markets

This research investigates that the price relationship between a stock index and its associated nearby futures markets can be explained by the cost-of-carry model using the concordance correlation (CC) coefficient in the US financial markets. The main purpose of this research is to confirm that the CC coefficient is an appropriate methodology to determine ex post arbitrage opportunities and to maximize ex ante arbitrage profits through the analysis of the price relationship derived from the cost-of-carry model. To increase the robustness of the results and to enable us to generalize our conclusions, this analysis is carried out in consideration of external uncertainty, including the marking-to-market procedure of futures contracts and the transaction cost on the stock index and its futures markets, under several assumptions related to the conditions of transactions. Examining transaction price data on the S&P 500 stock index and its futures markets shows that the CC coefficient gives a good result for ex ante arbitrage profits and is appropriate for analyzing the relationship between the observed stock index futures market price and its theoretical price derived from the cost-of-carry model.     

极端风险事件下股票市场与公司债券市场的尾部风险溢出研究——基于MVMQ-CAViaR模型

构建MVMQ-CAViaR模型,结合金融市场内部极端风险事件和外部极端风险事件,考量股票市场与公司债券市场的尾部风险溢出问题。结果表明,在金融市场内部极端风险事件下,股灾期间仅存在股票市场对公司债券市场单向的尾部风险溢出。公司债券违约潮期间,股票市场与公司债券市场之间存在双向不对称的尾部风险溢出,且公司债券市场对股票市...     

The Co‐movement of Credit Default Swap,Bond and Stock Markets: an Empirical Analysis

We analyse the relationship between credit default swap (CDS), bond and stock markets during 2000–2002. Focusing on the intertemporal co‐movement, we examine monthly, weekly and daily lead‐lag relationships in a vector autoregressive model and the adjustment between markets caused by cointegration. First, we find that stock returns lead CDS and bond spread changes. Second, CDS spread changes Granger cause bond spread changes for a higher number of firms than vice versa. Third, the CDS market is more sensitive to the stock market than the bond market and the strength of the co‐movement increases the lower the credit quality and the larger the bond issues. Finally, the CDS market contributes more to price discovery than the bond market and this effect is stronger for US than for European firms.     

The impact of terrorism on financial markets: An empirical study

The main focus of this paper is to study empirically the impact of terrorism on the behavior of stock, bond and commodity markets. We consider terrorist events that took place in 25 countries over an 11-year time period and implement our analysis using different methods: an event-study approach, a non-parametric methodology, and a filtered GARCH-EVT approach. In addition, we compare the effect of terrorist attacks on financial markets with the impact of other extreme events such as financial crashes and natural catastrophes. The results of our analysis show that a non-parametric approach is the most appropriate method among the three for analyzing the impact of terrorism on financial markets. We demonstrate the robustness of this method when interest rates, equity market integration, spillover and contemporaneous effects are controlled. We show how the results of this approach can be used for investors’ portfolio diversification strategies against terrorism risk.     

股指期货市场操纵与价格发现功能的关系研究

股指期货市场操纵会影响股指期货市场的价格发现功能,同样地,股指期货市场的价格发现功能也会影响股指期货市场的操纵行为。本文在理论探讨的基础上,利用股指期货主力合约及对应的沪深300指数高频数据对市场操纵行为进行实证分析。研究结果表明,当操纵嫌疑只存在于期货市场时,股指期货市场的价格发现功能将会减弱;当操纵嫌疑存在于期货、现货两个市场时,股指期货市场的价格发现功能相对会增强。而且,当股指期货市场价格发现功能较强时,市场操纵的难度和成本都将下降。当前中国股指期货市场的操纵行为可能主要局限于某些个别的、离散的交易日内,系统地通过操纵现货指数来操纵期货市场的可能性较低。     

Circuit Breakers,Trading Collars,and Volatility Transmission Across Markets: Evidence from NYSE Rule 80A

The NYSE's Rule 80A attempted to delink the futures and equity markets by limiting index arbitrage trades in the same direction as the last trade to reduce stock market volatility. Rule 80A leads to a small but statistically significant decline in intraday U.S. equity market volatility. In addition, the results are asymmetric: volatility is dampened more in a rising market than in a declining one. These results suggest that, to a limited extent, rule restrictions on trading can sufficiently delink the futures and equity markets enough to reduce the transmission of volatility.     

Correlation and return dispersion dynamics in Chinese markets

This paper studies the relation between firm-level return dispersions and correlations among Chinese stocks during periods of unusually large upward and downward swings. We analyze individual stock returns across 18 sectors and test if return dispersions and stock correlations show asymmetric patterns for extreme up and down markets. Evidence from studies on U.S. stocks suggests that equity return correlations tend to be much greater on the downside than on the upside and that the degree of comovement gets even stronger during extreme market states. However, in the case of Chinese stock market, we find that higher downside correlations apply to only stocks within the Financial sector. With the exception of Financial stocks, we find that stock correlations are significantly higher during up markets, rather than down markets. Regarding firm-level return dispersions, our findings are consistent with rational asset pricing model predictions. We find that equity return dispersions are significantly higher during periods of large price changes.     

Extreme spillover effect of COVID-19 pandemic-related news and cryptocurrencies on green bond markets: A quantile connectedness analysis

We provide the first empirical study on the role of panic and stress related to the COVID-19 pandemic, including six uncertainties and the four most traded cryptocurrencies, on three green bond market volatilities. Based on daily data covering the period from January 1, 2020 to January 31, 2022, we combine Diebold and Yilmaz's (2012, 2014) time domain spillover approach and Ando et al.'s (2022) quantile regression framework to investigate the time-frequency spillover connectedness among markets and measure the direction and intensity of the net transmission effect under extreme negative and positive event conditions, and normal states. We further provide novel insights into the green finance literature by examining sensitivity to quantile analysis of the net transfer mechanism between green bonds, cryptocurrencies, and pandemic uncertainty. Regarding the network connectedness analysis, the results reveal strong net information spillover transmission among markets under the bearish market. In extremely negative event circumstances, the MSCI Euro green bond acts as the leading net shock receiver in the system, whereas COVID-19 fake news appears as the largest net shock contributor, followed by BTC. According to sensitivity to quantile analysis, the net dynamic shock transfer mechanism is time-varying and quantile-dependent. Overall, our work uncovers crucial implications for investors and policymakers.     

Multiscale hedge ratio between the Australian stock and futures markets: Evidence from wavelet analysis

This paper examines the relationship between the Australian stock and futures markets over various time horizons. In contrast to methods employed in previous studies, wavelet analysis allows us to decompose data into various time scales. Using this technique and the Hurst exponent, we find that the Australian stock and futures markets are antipersistent. The wavelet correlation between the two markets varies over investment horizons, but remains very high. Furthermore, the magnitude of the correlation increases as the time scale increases, indicating that the stock market and the futures market of the All Ordinaries Index are found to be not fundamentally different. The hedge ratio increases as the wavelet time scale increases. In addition, the effectiveness of hedging strategies initially increases with the hedging horizon.     

Extreme dependence with asymmetric thresholds: Evidence for the European Monetary Union

Existing papers on extreme dependence use symmetrical thresholds to define simultaneous stock market booms or crashes such as the joint occurrence of the upper or lower one percent return quantile in both stock markets. We show that the probability of the joint occurrence of extreme stock returns may be higher for asymmetric thresholds than for symmetric thresholds. We propose a non-parametric measure of extreme dependence which allows capturing extreme events for different thresholds and can be used to compute different types of extreme dependence. We find that extreme dependence among the stock markets of ten initial EMU member countries, the United Kingdom, and the United States is largely asymmetrical in the pre-EMU period (1989–1998) and largely symmetrical in the EMU period (1999–2010). Our findings suggest that ignoring the possibility of asymmetric extreme dependence may lead to an underestimation of the probability of co-booms and co-crashes.