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.     

Empirical evidence of extreme dependence and contagion risk between main cryptocurrencies

This study examines the dependence and contagion risk between Bitcoin (BTC), Litecoin (LTC) and Ripple (XRP) using non-parametric mixture copulas (developed by Zimmer, 2012) and recently proposed methods of full-range tail dependence copulas (advanced by Hua, 2017, Su and Hua, 2017), for the period from 04-08-2013 to 17-06-2018. The Chi-plots and Kendall plots results show heavy tail dependence between each pairs of the cryptocurrencies. Evidence from the mixture copula indicates that for the BTC-LTC pair the upper-tail dependence is both stronger and more prevalent, while for the other pairs of cryptocurrencies the lower-tail dependence is very strong and more prevalent. However, the results of the full-range tail dependence copulas reveal a strong and prevalent upper and lower-tail dependence of each pairs of cryptocurrencies. These results provide evidence of significant risk contagion among price returns of major cryptocurrencies, both in bull and bear markets.     

Dividend announcements under varying market conditions: The case of specially designated dividends

In this study the author examines differences in the behavior of stock returns surrounding the announcements of the specially designated dividends (SDDs) between bull markets and bear markets. Results show that SDDs declared during bull markets have a significantly higher positive effect on stock prices than those declared during bear markets. This evidence, new to literature, indicates that SDDs declared during bull markets are viewed by the market as more favorable than those declared during bear markets.     

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.     

Economic policy uncertainty and stock market returns: New evidence

This paper investigates the predictive performance of the Chinese economic policy uncertainty (EPU) index constructed by Davis, Liu, and Sheng (2019) in forecasting the returns of China’s stock market. Using the univariate and bivariate predictive regression model, we confirm that the monthly EPU index can significantly and negatively impact the next month’s stock returns, and has better out-of-sample predictability than the existing EPU index and several macroeconomic variables. By comparing the forecasting effect of the EPU index before and during special events with sharply increased uncertainty, we find that the EPU’s forecasting power decline rapidly when an event of sharply increased uncertainty occurs. Finally, our conclusions are consistent through a batch of robustness tests.     

Stock market reactions to upside and downside volatility of Bitcoin: A quantile analysis

We investigate how sensitive developed and emerging equity markets are to volatility dynamics of Bitcoin during tranquil, bear, and bull market regimes. Intraday price fluctuations of Bitcoin are represented by three measures of realized volatility, viz. total variance, upside semivariance, and downside semivariance. Our empirical analysis relies on a quantile regression framework, after orthogonalizing raw returns with respect to an array of relevant global factors and accounting for structural shifts in the series. The results suggest that developed-market returns are positively related to the realized variance proxy across various market conditions, while emerging-market returns are positively (negatively) correlated with realized variance during bear (normal and bull) market periods. The upside (downside) component of realized variance has a negative (positive) influence on returns of either market category, and the dependence structure is highly asymmetric across the return distribution. Additionally, we document that developed and emerging markets are more sensitive to downside volatility than to upside volatility when they enter tranquil or bull territory. Our results offer practical implications for policymakers and investors.     

Asymmetric dependence structures for regional stock markets: An unconditional quantile regression approach

Owing to the asymmetry of stock markets, this study investigates the dependence structures for six regional stock markets according to different market conditions by applying the unconditional quantile regression (UQR) approach. This approach can address the traditional conditional quantile regression (CQR) approach’s limitation that its distributions are defined conditional on specific covariates. Specifically, we not only examine the detailed linkages among these six regional stock markets, but also explore the effect of global economic factors on them, given the strengthening of both international investment and the globalization of financial markets. The results show these dependence structures are often an asymmetric U-shaped or inverted U-shaped structure, which indicates that the impacts of both other geographically and economically close stock markets and economic factors are more pronounced during bear and bull markets than during normal markets, especially so in bear markets. Moreover, the UQR approach provides stronger extreme-value relationships and more significant asymmetric effects than the traditional CQR approach.     

Spillovers of currency carry trade returns,market risk sentiment,and U.S. market returns

This paper examines the link between spillovers of currency carry trade returns and U.S. market returns. Following Tse and Zhao (2012), this paper hypothesizes that the magnitude of spillovers of currency carry trade returns is positively correlated with market risk sentiment and, therefore, has an impact on market returns. Using the G10 currencies and S&P 500 index futures, the empirical results present a high magnitude of spillover effects of currency carry trade markets. The empirical findings also show a significantly positive relationship between spillovers of currency carry trade returns and subsequent market returns. Furthermore, the results indicate that this relationship is stronger in bear markets than in bull markets. Finally, our findings show that spillovers of currency carry trade returns significantly affect the subsequent transition probabilities of market returns.     

Do cryptocurrencies provide better hedging? Evidence from major equity markets during COVID-19 pandemic

Using the five-minute interval price data of two cryptocurrencies and eight stock market indices, we examine the risk spillover and hedging effectiveness between these two assets. Our approach provides a comparative assessment encompassing the pre-COVID-19 and COVID-19 sample periods. We employ copula models to assess the dependence and risk spillover from Bitcoin and Ethereum to stock market returns during both the pre-COVID-19 and COVID-19 periods. Notably, the COVID-19 pandemic has increased the risk spillover from Bitcoin and Ethereum to stock market returns. The findings vis-à-vis portfolio weights and hedge effectiveness highlight hedging gains; however, optimal investments in Bitcoin and Ethereum have reduced during the COVID-19 pandemic, while the cost of hedging has increased during this period. The findings also confirm that cryptocurrencies cannot provide incremental gains by hedging stock market risk during the COVID-19 pandemic.     

Is there one safe-haven for various turbulences? The evidence from gold,Bitcoin and Ether

This paper aims to investigate the safe-haven properties of gold and two cryptocurrencies, Bitcoin and Ether. Safe havens are the financial assets that allow investors to protect their portfolios within the market turmoil. The research sample covers five years and includes several downturns on the financial markets, starting from the Chinese stock market turbulences in 2015/2016 and ending up with the recent pandemic outbreak in 2020. We find that only gold used to be a strong safe-haven against the stock market indices. Yet, this property evaporated during the crisis caused by the COVID pandemic. Occasionally, cryptocurrencies could have been considered weak safe-havens against the examined instruments. Ether acted more often as a weak safe-haven against DAX or S&P500, while Bitcoin played this role against FTSE250, STOXX600 and S&P500.     

A simple framework for analysing bull and bear markets

Bull and bear markets are a common way of describing cycles in equity prices. To fully describe such cycles one would need to know the data generating process (DGP) for equity prices. We begin with a definition of bull and bear markets and use an algorithm based on it to sort a given time series of equity prices into periods that can be designated as bull and bear markets. The rule to do this is then studied analytically and it is shown that bull and bear market characteristics depend upon the DGP for capital gains. By simulation methods we examine a number of DGPs that are known to fit the data quite well—random walks, GARCH models, and models with duration dependence. We find that a pure random walk provides as good an explanation of bull and bear markets as the more complex statistical models. In the final section of the paper we look at some asset pricing models that appear in the literature from the viewpoint of their success in producing bull and bear markets which resemble those in the data. Copyright © 2002 John Wiley & Sons, Ltd.     

Great Places to Work®: Resilience in Times of Crisis

We study the resilience of the “100 Best Companies to Work for in America” in times of financial crisis by analyzing their long‐term financial performance. Apart from implementing methods that tackle the statistical problems of stock returns, we use a conditional model to measure financial performance in periods of market growth (bull markets) and market downturn (bear markets). We find that best places to work are indeed resilient in times of crisis since neither their financial performance nor their systematic risk are affected during bear markets: top companies continue to outperform the market during periods of crisis, and the performance of lower‐ranked great workplaces does not deteriorate. Moreover, we find that previous studies were overestimating performance, and only great workplaces on the top half of the rankings exhibit positive excessive returns. © 2015 Wiley Periodicals, Inc.     

Economic policy uncertainty effects for forecasting future real economic activity

Recently introduced measures for economic policy uncertainty (EPU), included in the data from 1997 to 2016, have a role in forecasting out-of-sample values for future real economic activity for both the euro area and UK economies. The inclusion of EPU measures, either for the US, the UK or for overall European economies, improves the forecasting ability of models based on standard financial market information, especially for the period before the 2008 global crisis. However, during and after the crisis period, the slope of the yield curve and excess stock market returns improves the out-of-sample forecast performance the most compared to an AR-benchmark model. Hence, the EPU information is important in times of normal business cycles, but might contain similar information components to financial market return variables during turbulent crisis periods in the financial markets and in the real economy.     

Time-frequency causality and dependence structure between crude oil,EPU and Chinese industry stock: Evidence from multiscale quantile perspectives

This article investigates the time-frequency causality and dependence structure of Chinese industry stock returns on crude oil shocks and China's economic policy uncertainty (EPU) across quantiles over the period from January 2001 to June 2021. We use wavelet-based decomposition series to establish a multiscale causality-in-quantiles test and a quantile-on-quantile regression approach to reveal the complicated relationships involving crude oil, EPU and stock returns. Our empirical results are as follows: First, the predictability of crude oil and EPU on industry stock returns is significantly strong under extreme market conditions. Second, the explanatory ability of EPU on industry stock returns in the long term is stronger than EPU’s ability to explain short term returns. Third, the impacts of crude oil and EPU on industry stock returns remain remarkably asymmetric across quantile levels. Finally, nonenergy-intensive industries are also affected by crude oil shocks, but less than energy-intensive industries. Overall, these empirical findings can provide implications for policymakers to stabilize stock markets and investors to hedge the potential risks from crude oil and EPU.     

Broad-based stock options: before and after the market downturn

We examine labour productivity in small, medium and large firms that broadly distribute stock options under starkly different market conditions – during the bull (1995–7) and bear (2000–2) stock markets. We find greater labour output in both upward and downward markets in all firm size categories, with the exception of small firms in a declining market, where the productivity is also greater, but the statistical significance of the result is weak.     

Individual stock sentiment beta and stock returns

Using the data in Chinese stock market, we measure the individual stock sentiment beta, which is defined as the sensitivity of individual stock returns to the individual stock sentiment changes. We demonstrate that stocks in the highest individual stock sentiment beta portfolio have significantly higher excess returns, CAPM alpha, Fama-French three-factor alpha and Fama-French five-factor alpha. Besides, we find that the high individual stock sentiment beta stocks are smaller, younger, more volatile stocks with higher price and higher market beta. After controlling for firm characteristic, the returns of High-Low individual stock sentiment beta portfolios are still significantly positive. Moreover, we show the effect of the individual stock sentiment beta on stock returns is positive and significant in different stock markets, in different sample periods, and in bull and bear market. Besides, the results of the Bayes-Stein individual stock sentiment beta are still stable.     

Does US news impact Asian emerging markets? Evidence from nonparametric causality-in-quantiles test

This paper aims to analyze whether US news on inflation and unemployment causes returns and volatility of seven emerging Asian stock markets from 1994 to 2014, by employing the causality-in-quantile approach. We find evidence that US news affect returns and/or volatility of all the seven stock markets considered, with these effects clustered around the tails of the conditional distribution of returns and volatility when they are either in bear or bull modes. In general, our results highlight the importance of modeling nonlinearity and studying entire conditional distributions of stock returns and volatility to draw correct inferences.     

国内外黄金市场收益长记忆性比较研究\n——基于重标方差分析法

利用重标方差分析法,对比研究英国伦敦和中国上海黄金市场收益的长记忆性的结果表明：对于不同的q值,国内外黄金市场日收益率都存在显著的长记忆性。相比较而言,英国伦敦黄金市场日收益率的长记忆性更强。产生这一现象的深层原因在于我国黄金价格形成机制受到了较多的政府调控,而并不能简单地说我国黄金市场的效率高于英国伦敦黄金市场。     

The strength and source of asymmetric international diversification

We find that correlations between international markets continue to increase over time compared to previous research, with only Asian markets providing lower correlations relative to American and European markets. Consistent with previous studies, the benefits from international diversification are asymmetric, with reduced diversification benefits during bear markets. We extend previous results by examining the characteristics and causes of the returns affecting these asymmetric correlations, relating these results to the herding behavior of investors across markets rather than to fundamental economic reasons. Specifically, we determine that the increase in correlations among markets is most closely associated with the larger correlations from the largest positive return time intervals in bear markets rather than the negative returns. Use of stock index futures avoids issues inherent in the use of international cash indexes.     

Pricing efficiency and asymmetric multifractality of major asset classes before and during COVID-19 crisis

We examine the impact of COVID-19 pandemic crisis on the pricing efficiency and asymmetric multifractality of major asset classes (S&P500, US Treasury bond, US dollar index, Bitcoin, Brent oil, and gold) within a dynamic framework. Applying permutation entropy on intraday data that covers between April 30, 2019 and May 13, 2020, we show that efficiency of all sample asset classes is deteriorated with the outbreak, and in most cases this deterioration is significant. Results are found to be robust under different analysis schemes. Brent oil is the highest efficient market before and during crisis. The degree of efficiency is heterogeneous among all markets. The analysis by an asymmetric multifractal detrended fluctuation analysis (A-MF-DFA) approach shows evidence of asymmetric multifractality in all markets which rise with the scales. The inefficiency is higher during downward trends before the pandemic crisis as well as during COVID-19 except for gold and Bitcoin. Moreover, the pandemic intensifies the inefficiency of all markets except Bitcoin. Findings reveal increased opportunities for price predictions and abnormal returns gains during the COVID-19 outbreak.