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.     

Geopolitical risks and stock market dynamics of the BRICS

This paper examines the effect of geopolitical uncertainty on return and volatility dynamics in the BRICS stock markets via nonparametric causality-in-quantiles tests. The effect of geopolitical risks (GPRs) is found to be heterogeneous across the BRICS stock markets, suggesting that news regarding geopolitical tensions do not affect return dynamics in these markets in a uniform way. GPRs are generally found to impact stock market volatility measures rather than returns, and often at return quantiles below the median, indicating the role of GPRs as a driver of bad volatility in these markets. While Russia bears the greatest risk exposure to GPRs in terms of both return and volatility, India is found to be the most resilient BRICS nation in the group. Noting that geopolitical shocks and in particular terrorist incidents are largely unanticipated, our findings underscore the importance of a strong financial sector that can help return the market to stability and an open economy that allows local investors to diversify country-specific risks in their portfolios.     

Is there a risk–return trade‐off? Evidence from high‐frequency data

This paper examines the intertemporal relation between risk and return for the aggregate stock market using high‐frequency data. We use daily realized, GARCH, implied, and range‐based volatility estimators to determine the existence and significance of a risk–return trade‐off for several stock market indices. We find a positive and statistically significant relation between the conditional mean and conditional volatility of market returns at the daily level. This result is robust to alternative specifications of the volatility process, across different measures of market return and sample periods, and after controlling for macro‐economic variables associated with business cycle fluctuations. We also analyze the risk–return relationship over time using rolling regressions, and find that the strong positive relation persists throughout our sample period. The market risk measures adopted in the paper add power to the analysis by incorporating valuable information, either by taking advantage of high‐frequency intraday data (in the case of realized, GARCH, and range volatility) or by utilizing the market's expectation of future volatility (in the case of implied volatility index). Copyright © 2006 John Wiley & Sons, Ltd.     

Positive IVOL-MAX effect: A study on the Singapore Stock Market

This paper demonstrates a positive and significant IVOL effect in the Singapore Stock Market meaning that the highly volatile stocks are showing better returns in the subsequent month. More explicitly, there is a strong positive relationship between stock’s idiosyncratic volatility (IVOL) and its subsequent month’s return in the Singapore equity market. This positive IVOL effect is stronger only for small market-statistic firms. But for the Large capital firms, the positive IVOL effect is insignificant. In addition, this paper shows that the relationship between maximum daily return over a month (MAX) and the subsequent month’s return is positive and significant in this market. However, IVOL is the true effect of this market rather than MAX.     

The momentum and reversal effects of investor sentiment on stock prices

In this paper, we illustrate the real function relationship between the stock returns and change of investor sentiment based on the nonparametric regression model. The empirical results show that when the change of investor sentiment is moderate, the stock return is positively correlated with the change of investor sentiment, presenting an obvious momentum effect. However, the stock return is negatively correlated with the change of investor sentiment if the change of investor sentiment is dramatic, presenting significant reversal effects. Moreover, the degree of reversal effect caused by extremely optimistic sentiment is greater than that driven by extremely pessimistic sentiment, which shows a significant asymmetry. Our findings offer a partial explanation for financial anomalies such as the mean reversion of stock returns, the characteristic of slow rise and steep fall in China's stock market and so on.     

Time–frequency quantile dependence between Bitcoin and global equity markets

In this paper, we examine return dependence between Bitcoin and stock market returns using a novel quantile cross-spectral dependence approach. The results suggest a right-tail (high return) dependence between Bitcoin and the stock markets in the long term and that said dependence decreases significantly from yearly to monthly investment horizons. Furthermore, right-tail dependence between Bitcoin and the US stock market is the strongest compared with other stock markets. We also extract information on the time-varying and time–frequency structure of co-movements between Bitcoin and the stock markets using wavelet-coherence analysis, the results of which suggest that the co-movement between Bitcoin and the US stock market is positive, whereas, for other stock markets, it is negative at certain frequencies and time periods. Overall, the findings highlight additional risk-management capabilities of Bitcoin according to different stock markets.     

The stock–bond comovements and cross-market trading

We propose an asset pricing model with heterogeneous agents allocating capital to the stock and bond markets to optimize their portfolios, utilizing the dynamic interaction between the two markets. While some agents focus on the stock market and have more expertise in it, the others specialize in the bond market. Based on their comparative advantages in a particular market, heterogeneous agents constantly revise their investment portfolios by taking into account the time-varying stock–bond return comovements and the changing market conditions. Agents׳ collective investment behavior shapes the stock–bond interlinkage, which feedbacks on their subsequent capital allocations. Using monthly US stock and bond data from January 1990 to June 2014, we estimate the vector autoregression model with threshold and Markov switching mechanisms. We find evidence in support of flight-to-quality and show that it is mainly driven by the technical traders who actively sell stocks and buy bonds during periods of high market uncertainty.     

Sovereign rating changes—Do they provide new information for stock markets?

The purpose of this paper is to examine the impact of sovereign rating changes on international financial markets using a comprehensive database of 42 countries, covering the major regions in the world over the period 1995–2003. In general, we find that rating agencies provide stock and foreign exchange markets with new tradable information. Specifically, rating upgrades (downgrades) significantly increased (decreased) USD denominated stock market returns and decreased (increased) volatility. Whereas the mean response is contributed evenly by the local currency stock returns and exchange rate changes that make up the USD returns, only the foreign exchange volatility was behind the USD denominated return volatility. In addition, we find significant asymmetric effects of rating announcements. The market responses – both return and volatility – are more pronounced in the cases of downgrades, foreign currency debt, emerging market debt, and during crisis periods. This study has important policy implications for international investors’ asset allocation plans and for regulatory bodies such as the Basel Committee who increasingly rely upon Moody's, Standard and Poor's and Fitch's ratings for their regulatory regimes.     

中国股票市场国际联动性研究

本文选取2000~2015年全球40支股票指数日收盘价,通过建立收益率网络和DCC MVGARCH模型波动率网络对中国股票市场国际联动性进行实证分析。研究表明,随着经济全球化的加深,全球股市收益率和波动率联动逐渐增强;全球金融危机和欧债危机期间,收益率联动网络具有小世界性;中国与全球股市长期处于割裂状态,但在全球金融危机期间与其他市场联系加强。在全球经济形势复杂多变的情况下,中国应针对性采取措施促进股市发展,以分享全球金融一体化利益。     

Does weather impact the stock market? Empirical evidence in Taiwan

Psychological evidence suggests close relationships between weather and mood. Individuals feel in a more positive frame of mind on sunny than cloudy days. This study applies GJR–GARCH to examine the relationship among weather, stock returns and risk in Taiwan from 2001 to 2007. The empirical results indicate that precipitation does not significantly influence stock return and risk; likewise, sunshine hours and temperature insignificantly influence stock return, but do significant impact stock risk. These findings demonstrate that weather effect really exist in stock market, and can help investors in making innovative investment and management decisions.     

Infectious diseases tracking and sectoral stock market returns: A quantile regression analysis

This paper investigates the relationship between changes in the newspaper-based infectious diseases tracking index (ITI) of Baker et al. (2020) and sectoral stock market returns in the US. Our results spanning the period 1985:01 to 2020:03 reveal the presence of a negative (positive) relationship between returns and ITI at lower (higher) return quantiles (representing different market conditions) in a majority of the sectors. For the health care sector, this relationship is negative at all quantiles. Interestingly, inclusion of the COVID-19 period in the sample data leads to the detection of a stronger relationship for smaller quantiles across all sectors. An asymmetric relationship between returns and the ITI is witnessed across different market conditions for the Consumer Staples, Healthcare, Industrial and Technology sectors. Results from a rolling regression uncover differences in the magnitudes of responses to various infectious diseases over time. Our results carry important implications regarding investment strategies for US sectoral returns in the presence of news relating to infectious diseases.     

Firm Characteristics and Chinese Stocks

This paper presents a comprehensive study on predicting the cross section of Chinese stock market returns with a large panel of 75 individual firm characteristics. We use not only the traditional Fama-MacBeth regression, but also the “big-data” econometric methods: principal component analysis (PCA), partial least squares (PLS), and forecast combination to extract information from all the 75 firm characteristics. These characteristics are important return predictors, with statistical and economic significance. Furthermore, firm characteristics that are related to trading frictions, momentum, and profitability are the most effective predictors of future stock returns in the Chinese stock market.     

Compensation for illiquidity in China: Evidence from an alternative measure

This paper shows that liquidity is an important source of priced risk in China. Using A-share stocks in Shanghai and Shenzhen Exchange over the period 2007–2017, we examine the influence of liquidity on stock returns. A new liquidity measure that captures multiple dimensions of liquidity is proposed. Fama-Macbeth cross-sectional regression shows that the expected return is negatively correlated with liquidity. Based on Fama and French (1993), we propose a five-factor pricing model by incorporating reversal factor and liquidity factor. Time-series regressions show that the liquidity factor makes significantly marginal contributions to explaining excess stock returns. The liquidity factor based on the proposed measure works better than alternative liquidity measures such as turnover, Amihud illiquidity measure and the measure in Liu (2006).     

年报信息披露的超常收益及其影响因素

与年报盈余公告效应的研究不同,本文在拓展年报信息考虑范围的基础上,检验盈余信息、股利信息、账市比、成长性和财务风险等年报披露信息对不同公司规模的超常收益的解释能力。研究结果表明,年报信息披露窗口存在显著超常收益,账市比、盈余信息、股利信息对该超常收益有显著的解释能力,因为在大多数公司规模中,账市比、盈余信息的极端值含有股票未来收益的信息,账市比、盈余信息、股利信息对超常收益有显著的边际影响;但成长性和财务风险等年报信息仅对部分公司规模的超常收益有解释能力。     

Macroeconomic influences on the stock market

The paper studies the dynamic interactions among indicators of economic activity, such as industrial production, interest rate and exchange rate, the performance of the foreign stock market, oil prices, and stock returns to examine whether economic activity movements affect the performance of the stock market for Greece. The empirical evidence suggests that stock returns do not lead changes in real economic activity while the macroeconomic activity and foreign stock market changes explain only partially stock market movements. Oil price changes explain stock price movements and have a negative impact on macroeconomic activity.     

Market efficiency, discount-rate changes, and stock returns: A long-term perspective

This paper examines the market efficiency issue by analyzing stock returns surrounding Fed announcements of discount-rate changes. Based on an analysis ofex post returns over a 58-year period, the results provide evidence of long-term market efficiency. Consistent with recent literature, the findings also reveal some predictability in return patterns where an active trading strategy based on directional reversals in the pattern of discount rate changes outperforms a passive buy-and-hold approach. The results indicate that the proposed active trading produces substantially higher risk-adjusted returns than the buy-and-hold strategy.     

Shifts in volatility driven by large stock market shocks

This paper presents an extension of the stochastic volatility model which allows for level shifts in volatility of stock market returns, known as structural breaks. These shifts are endogenously driven by large return shocks (innovations), reflecting large pieces of market news. These shocks are identified from the data as being bigger in absolute terms than the values of two threshold parameters of the model: one for the negative shocks and one for the positive shocks. The model can be employed to investigate different sources of stock market volatility shifts driven by market news, without relying on exogenous information. In addition to this, it has a number of interesting features which enable us to study the effects of large return shocks on future levels of market volatility. The above properties of the model are shown based on a study for the US stock market volatility.     

Aggregate stock market behavior and investors’ low risk aversion

This paper studies whether investors’ high risk aversion can be avoided in a representative-agent model that is able to explain aggregate stock market behavior in the US financial market. We present a consumption-based asset pricing model with a representative agent who has a ‘catching up with the Joneses’ preference to show that high risk aversion can be avoided in a representative-agent model that can help explain many of the empirically observed properties of the aggregate stock market return, including the equity premium and risk-free rate puzzles, the predictability of long-horizon stock returns, and the ‘leverage effect’ in return volatility.     

Contestability of the urban land market: an event study of Hong Kong land auctions

The traditional theory of urban land markets assumes perfect contestability—the absolute freedom of market entry—that compels developers to bid up the land rent to equal the economic profit from land use. This assumption, however, is empirically untested due to the difficulties in measuring the ex ante economic profit of land acquisition. We overcome these difficulties by applying the event-study methodology to Hong Kong government land auctions. When a developer acquires a site at a price below its fair market value, the rationality of the stock market entails a positive abnormal return on the developer’s stock. Our analysis shows evidence of positive expected abnormal returns, indicating an imperfectly contestable land market. We further show that the expected abnormal return increases with the site value and the government land disposal level but decreases with the property market liquidity.     

Analysis of the impact of Sino-US trade friction on China’s stock market based on complex networks

This paper analyzes the impact of the Sino-US trade friction incident in 2018 on China's stock market by using the complex network methods. Firstly, we divide the Sino-US trade friction incident in 2018 into four research periods. Based on the GARCH-BEKK model and the Planar Maximum Filter Graph (PMFG) algorithm, the volatility spillover network between China's stock market sectors and the stock price correlation network of China's stock market corresponding to the above four research periods are constructed. Next, from the perspective of sectors in stock market, we use various network centrality indicators to build a systematic importance comprehensive evaluation index of industry sectors in the stock market through the principal component analysis method, to explore the impact of the Sino-US trade friction incident on the risk spillover effects of sectors in China's stock market. From the perspective of the overall stock market, we analyze the impact of Sino-US trade friction incident on the overall stability of the stock market through calculating the network topology indicators and conducting simulation experiments. Finally, the main factors affecting the stability mechanism of China's stock market are studied through the probit model. The results show that: (1) The risk spillover effect of various sectors in China's stock market changes significantly in different periods of Sino-US trade friction, and there are obvious cyclical rotation effects among various sectors (2) When some weighted stocks in the stock market abnormally fluctuate or suffer targeted shocks, the China's stock market's ability to maintain stability is weak, and the Sino-US trade friction will reduce the stability of China's stock market, and the higher the intensity of trade friction incident is, the more obvious the impact of the incident is. (3) The important factors that affect the abnormal fluctuations in China's stock market include four types of indicators: the stock market network structure, the fluctuation of important international stock indexes, the fluctuation of commodity prices in the international market, and the domestic macroeconomic indicators. This study provides a reference for China's financial regulatory authorities to conduct macro-prudential management, control systemic risks, and maintain the stability of financial market.