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。     

Do hedge funds time market tail risk? Evidence from option-implied tail risk

This paper focuses on an unexplored dimension of fund managers’ timing ability: Market-wide tail risk implied by information in options markets. Constructing the option-implied tail risk, we investigate whether hedge fund managers can strategically time the tail risk through adjusting their exposure to changes of it. Using an extensive sample of equity-oriented hedge funds, we find strong evidence of tail risk timing ability of hedge fund managers. Furthermore, tail risk timing ability brings significant economic value to investors. Top-ranked funds outperform bottom-ranked funds by 5–7% annually after adjusting for risk factors. Our results are robust to various robustness checks.     

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.     

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.     

Stock market dependence in crisis periods: Evidence from oil price shocks and the Qatar blockade

This paper examines the correlation and the dependence patterns of the Qatar stock market with other markets using copula statistical theory and exploiting new datasets covering the period August 1998 to June 2018. To examine the crisis –specific change in the average degree of dependence we decomposed the data into the time periods before and after oil price shocks and the 2017 political crisis among the Gulf Cooperation Council members (i.e. the Qatari blockade). Our findings from the static copula modelling show that the correlations between the Qatari and the other stock markets significantly change after the oil price and the blockade crisis as well. The degree of change in the correlation is time varying and differs from county-group to another. Moreover, our findings reveals that the 2008 global financial crisis has a stronger impact than the price shocks and political crisis. The findings of the paper are of interest and allow for formulating a reliable and dynamic portfolio design framework for investors and risk managers.     

Trading timing and the returns to trend-following

We document a negative impact of realistic trading timing on trend-following profits, across an international sample of equity indexes and stocks. The discount effect is substantial but reduces as trend signals become less accurate. The size of this trading timing bias is largely driven by the volatility of buy-and-hold returns and that of trend signals.     

Bubbles for Fama

We evaluate Eugene F. Fama's claim that stock prices do not exhibit price bubbles. Based on US industry returns (1926?2014) and international sector returns (1985?2014), we present four findings (1) Fama is correct in that a sharp price increase of an industry portfolio does not, on average, predict unusually low returns going forward; (2) such sharp price increases predict a substantially heightened probability of a crash but not of a further price boom; (3) attributes of the price run-up, including volatility, turnover, issuance, and the price path of the run-up, help forecast an eventual crash; and (4) these attributes also help forecast future returns. Results hold similarly in US and international samples.     

Jensen's alpha and the market‐timing puzzle

Theory predicts that market‐timing activities bias Jensen's alpha (JA). However, empirical studies have failed to find consistent evidence of this bias. We tackle this puzzle in a nested model analysis and show that the bias contains an exogenous market component that is unrelated to market‐timing skill. In a comprehensive empirical analysis of US mutual funds, we find that the timing‐induced bias in JA is mainly driven by this market component, which is uncorrelated with measured timing activities. Measures of total performance that allow for timing activities are virtually identical to JA, even if timing activities are present in the evaluated fund. Hence, we conclude that JA is a sufficient measure of total performance.