Stock market reactions to monetary policy surprises under uncertainty

This article investigates how uncertainty impacts the effect of monetary policy surprises on stock returns. Using high-frequency US data, we demonstrate that stock markets respond more aggressively to monetary policy surprises during periods of high uncertainty. We also show that uncertainty asymmetrically influences the transmission of positive and negative monetary policy surprises to stock market prices. The amplifying effect of uncertainty is found to be stronger for expansionary shocks than for contractionary shocks. Our robustness analysis confirms that financial uncertainty has a significant role in shaping the influence of monetary policy on the stock market.     

中国家庭股市资产价值变动对居民消费的影响——来自CHFS的微观证据

近年来针对股市资产价值变动与消费关系的研究多采用宏观数据，难以揭示股市资产价值变动对居民消费影响的细节。为克服以上缺陷，文章利用中国家庭金融调查（CHFS）数据分析股市资产价值变动对中国居民消费的影响。实证结果表明：（1）股市资产价值变动对居民消费的影响总体较弱，其中市值变动的财富效应主要体现在改善性消费上，而对饮食等日常必须消费和奢侈品消费影响较小，这可能与我国居民的收入结构和投资方式有关；（2）随着年龄增长，居民的收入分布和资产配置倾向发生改变，股市资产价值变动对不同年龄居民消费的影响呈现先减小后增大的U型分布。研究结论揭示了股市资产价值变动对居民消费影响的分布特征，为今后股市改革方向提供了建议。     

颠覆性创新四阶段扩散过程模型

基于颠覆性创新、创新扩散、创新模糊前端等相关理论，从全流程角度创新性地构建了颠覆性创新四阶段扩散过程模型，包括颠覆性创意产生、颠覆性创新产品开发、侵蚀非主流市场、占据主流市场4个阶段，各阶段之间相互关联、循环往复，并受到技术、市场、政策、竞争等外部环境因素影响。选取液晶电视机和山寨手机作为高端和低端两个颠覆性创新典型案例，通过对其进行验证性分析，构建具体的高端与低端颠覆性创新四阶段扩散过程模型。     

Volatility forecasting: long memory,regime switching and heteroscedasticity

In this article, we account for the first time for long memory, regime switching and the conditional time-varying volatility of volatility (heteroscedasticity) to model and forecast market volatility using the heterogeneous autoregressive model of realized volatility (HAR-RV) and its extensions. We present several interesting and notable findings. First, existing models exhibit significant nonlinearity and clustering, which provide empirical evidence on the benefit of introducing regime switching and heteroscedasticity. Second, out-of-sample results indicate that combining regime switching and heteroscedasticity can substantially improve predictive power from a statistical viewpoint. More specifically, our proposed models generally exhibit higher forecasting accuracy. Third, these results are widely consistent across a variety of robustness tests such as different forecasting windows, forecasting models, realized measures, and stock markets. Consequently, this study sheds new light on forecasting future volatility.     

Fancy Bitcoin and conventional financial assets: Measuring market integration based on connectedness networks

We investigate the relationship between Bitcoin and conventional financial assets from a perspective on the connectedness of asset networks. We adopt the method of measuring connectedness proposed by Diebold and Yilmaz (2009, 2012, and 2014) in a VAR system to study the dynamic interdependence between returns in Bitcoin, stocks, oil, and gold. We find that the connectedness between bitcoin and conventional assets is weak. The separation of positive and negative returns in the Bitcoin market shows the existence of an asymmetric pattern of the spillover effects between Bitcoin and conventional assets. A rolling window analysis finds that although Bitcoin prices experience a rising link to other financial assets, the magnitude is proven to be moderate. However, connectedness via negative returns is much stronger than via positive ones and exhibits a clearly increasing trend in recent periods. Our results in application are generally robust to other popular cryptocurrencies, such as ETH and Ripple. The findings presented in this paper have important implications for financial market participants, policymakers, and researchers in light of projected increases in the adoption of Bitcoin, as well as the rapid development of cryptocurrency.     

Stock price crash risk and CEO power: Firm-level analysis

This study examines the impact of stock price crash risk on future CEO power. Using a large panel sample with 17,816 firm-year observations, we posit and find a significant negative impact of stock price crash risk on CEO power, suggesting that CEO power becomes smaller after stock price crashes. We also find that our results are stronger for firms with female CEOs and are largely driven by firms with shorter-tenure CEOs. In addition, we find that the significant negative impact of stock price crash risk on CEO power is diminished for firms with strong corporate governance. Our study responds to the call in Habib, Hasan, and Jiang (2018) by providing more empirical evidence on the consequences of stock price crash risk.     

The price of going green: the role of greenness in green bond markets

In this paper, we empirically investigate how greenness information is priced in the green bond market. Our comparison of liquidity-adjusted yield premiums of green bonds versus synthetic conventional bonds indicates that, on average, there is no robust and significant yield premium or discount on green bonds. However, green bonds certified by an external reviewer enjoy a discount of about 6 bps. Furthermore, green bonds that obtain a Climate Bonds Initiative certificate show a discount of around 15 bps. The findings suggest that a universally accepted greenness measure can benefit the development of the green bond market.     

How efficient is the market for Australian firms’ earnings information?

We construct a measure of the speed with which forecasts issued by sell-side analysts accurately forecast future annual earnings. Following Marshall, we label this measure earnings information flow timeliness (EIFT). This measure avoids the aggregation problem inherent in price-based measures of information efficiency. We document large variation in EIFT across firm-years, and show that EIFT is positively associated with the extent of analyst following, consistent with increased analyst coverage improving the speed with which earnings-related information is recognised. We also find that EIFT is higher for firm-years classified as ‘bad news’ (i.e., where analysts’ forecasts at the start of the financial period exceed the reported outcome). However, when we separately consider instances where analysts appear to forecast non-GAAP (or ‘street’) earnings rather than GAAP earnings, we find that the greater timeliness of bad news is concentrated among observations where analysts forecast non-GAAP earnings, where unusual items are typically excluded. We conclude that the market for accounting information is more efficient for negative operating outcomes than for negative outcomes reflecting unusual items.     

Environmental,social, and governance practices and perceived tail risk

Using the implied volatility smirk on individual equity securities to measure perceived tail risk, we find that better environmental, social and governance (ESG) practices significantly reduce ex-ante expectations of a left-tail event. Our findings are robust to using multiple model specifications and to adjusting for potential endogeneity concerns. We also show that, while practices in each ESG pillar are important in reducing perceived tail risk, the environmental pillar plays the most important role. Our results indicate that investors consider strong ESG practices to be insurance against left-tail events rather than wasteful investment borne out of managers’ own values or self-interest.