我国股票期现货市场间的溢出效应研究--基于1分钟高频数据的实证检验

本文以我国沪深300股指期现货为研究对象,采用2012年4月16日—2014年3月20日的1分钟高频交易数据,通过构建多元DCC-VARMA-GARCH模型检验了我国股指期现货市场之间的溢出效应。实证结果表明,我国股指期现货市场之间存在双向波动溢出效应,且现货市场的波动溢出效应大于期货市场,而均值溢出效应仅表现为期货市场向现货市场的单向传递。这说明我国股指期货市场已具备基本的价格发现功能,发挥了稳定股票现货市场的作用。     

The First‐ and Second‐Hand Effect of Analysts' Stock Recommendations: Evidence from the Swiss Stock Market

This paper empirically investigates the impact of both the first release of analysts' stock recommendations to a limited clientele and the subsequent dissemination of the same information in a major newspaper to a broader audience. For a sample of 1460 stock recommendations published in FuW, Switzerland's major financial newspaper, significant positive abnormal returns on the day of the original release of buy recommendations and on the day of publication in FuW are documented. Tests of the price pressure and information hypotheses reveal that analysts' recommendations contain new information, which is quickly incorporated in the stock prices on the first release of this information. In contrast, the statistically significant announcement effects associated with the subsequent publication can be primarily ascribed to price pressure in the underlying securities.     

Conference Calls and Stock Price Volatility in the Post‐Reg FD Era

Past research has documented that the utilisation of conference calls is greater in the high tech sector than in other industries. Do high tech firms benefit from that? This study attempts to answer this question by examining the impact of ‘post‐Reg FD’ conference calls on the price volatility of high tech firms listed in the US market. We find evidence that more open conference calls results in lower idiosyncratic volatility.     

Real‐Time Forecasting and Political Stock Market Anomalies: Evidence for the United States

Using monthly data from 1953 to 2003, we apply a real‐time modeling approach to investigate the implications of U.S. political stock market anomalies for forecasting excess stock returns in real‐time. Our empirical findings show that political variables, chosen on the basis of widely used model‐selection criteria, are often included in real‐time forecasting models. However, political variables do not contribute systematically to improving the performance of simple trading rules. For this reason, political stock market anomalies are not necessarily an indication of market inefficiency.     

The Cross-Sectional Relationship Between Trading Costs and Lead/Lag Effects in Stock & Option Markets

Prior empirical research has failed to settle the question of lead/lag effects between stock and option markets. This study investigates the relation between cross-sectional differences in trading costs and intraday lead/lag effects in stock and option markets. The data for the study comprise 19 firms sampled at five-minute intervals over a two-month period. Consistent with a trading cost hypothesis, results indicate overall stock market leading behavior. However, the lead appears to be related to option market trading costs. This study uses an error correction model framework to investigate the lead/lag effects. This approach provides information on both the long run equilibrating process as well as the short term interactions between stock and option markets. Information regarding the long run equilibrating process is important to the overall understanding of lead/lag effects and cannot be determined from time series models of differenced data. Specific criteria for assessing lead/lag effects in cointegrated series are also proposed. One advantage of these new criteria is their ability to identify leading behavior in the presence of feedback. All models are estimated with quote data and are constructed to eliminate overnight effects. Hence, the results are robust to previously identified distortions due to closing, overnight, and potential non-trading effects. However, caution should be employed in generalizing the results as the study covers a two-month trading period for a limited number of firms.     

Investor sentiment‐styled index in index futures market

In this paper, we define and analyze the sentiment‐styled index for the CSI 300 index futures in the Chinese futures market. Our sentiment‐styled index for the CSI 300 index futures from April 16, 2010 to April 30, 2019 is constructed by the first and second principal component analyses, rather than only by the first principal component analysis used in the Baker and Wurgler (Journal of Finance 61(4): 1645–1680, 2006) method. The sentiment‐styled index explains 78.38% of the sample variance. The vector error correction model is adapted to study the dynamics of cointegration of the sentiment‐styled index and the logarithmic futures price. We use the GARCH‐DCC model to illustrate the spillover effect between the sentiment‐styled index and the Chinese futures market. We show that this investor sentiment‐styled index does have the price discovery from the Granger causality and common factor weights and the hedging function from the Baba–Engle–Kraft–Kroner model empirically; furthermore, we use the curvature term of the sentiment‐styled index to determine the multiple unit roots. More empirical results for the sentiment‐styled index of the Chinese stock market, the sentiment‐styled index of the CSI 300 index futures, and the return of the CSI 300 index futures market are studied in this paper.     

The Core,Periphery, and Beyond: Stock Market Comovements among EU and Non‐EU Countries

Using linear and nonlinear correlations, copulas, quantile dependence and lower tail dependence, we find that (1) equity markets of the advanced European Union (EU) countries comove more closely with each other than with the peripheral economies, (2) comovements with non‐EU countries are lower, (3) relative comovement structure before, during, and after the global financial crisis has been very stable, and (4) the level of comovements remained virtually the same between the crisis and post‐crisis periods. Our results are robust to controlling for Fama‐French, U.S. and global risk factors, as well as monetary policy, market interest rates, exchange rates, and uncertainty.     

Incentive‐compatible contracts in merger negotiations: The role of acquirer idiosyncratic stock return volatility

We show that the acquiring firm's idiosyncratic stock return volatility (sigma) is an important determinant of the selection and perceived valuation effects of earnouts in Mergers and Acquisitions (M&As). Earnout‐based M&As are more often announced by high‐sigma acquirers (nearly 40% of all earnout‐based M&As), yet the documented higher risk‐adjusted returns accrued to acquirers in earnout‐based M&As, relative to M&As settled in cash, stock or mixed payments (the earnout effect), appear in deals announced by low‐sigma acquirers (nearly 20% of all earnout‐based M&As). High‐sigma acquirers employing earnouts appear to break even, or even experience losses, relative to their counterparts employing single up‐front payments. These results are confirmed based on a quasi‐experimental design through which the earnout effect is measured in isolation. We argue that in M&As announced by high‐sigma acquirers, the earnout effect is potentially elusive due to the presence of an acquirer‐specific information revelation effect, resulting from the heightened extent of information asymmetry between (small) acquirers’ managers and outside investors. On the contrary, the use of earnouts in M&As announced by low‐sigma (large) acquirers, whereby the acquirer‐specific information revelation effect is likely negligible, sends a strong signal for value creation that also prevents investors from inducing a size‐related discount.