Are the Best Small Companies the Best Investments?

Previous research finds that large companies previously judged to be excellent growth companies have subsequently been poor investments. We examine small companies selected by Business Week on the basis of multiple criteria used in annual articles featuring highly rated growth companies. We study the investment performance over the three years before eleven annual Business Week publications and the three years after publication. We find positive excess returns in the pre‐publication period, but negative excess returns in the post‐publication period. This reversal in investment performance appears to be due to a mean‐reversion tendency in operating performance, in which the earnings and the past rates of return on capital of such companies subsequently decrease significantly.     

ALL THINGS CONSIDERED,TAXES DRIVE THE JANUARY EFFECT

The multitude of explanations for the January effect leaves the reader confused about its primary cause(s): is it tax‐loss selling, window dressing, information, bid‐ask bounce, or a combination of these causes? The confusion arises, in part, because evidence has generally been presented in support of a particular hypothesis though the same evidence may be consistent with another hypothesis. Furthermore, prior work does not adequately control for the bid‐ask bounce. In this article we try to disentangle different explanations of the January effect and identify its primary cause. We find that tax‐related selling is the most important cause, overshadowing other explanations.     

On the Statistical Significance of Event Effects on Unsystematic Volatility

We develop a method for determining the significance of the effect of a certain event (stock split, corporate restructuring, change in regulation, etc.) on unsystematic volatility of asset returns. Simulations show that the suggested tests reject the true null hypothesis of no effect on volatility at appropriate levels, whereas the rejection rates of a false null hypothesis increase with the magnitude of the effect. An application of the method to corporate spin‐offs reveals statistically significant and long‐lasting estimated increases in unsystematic volatility of parent companies' returns.     

露天边坡工程及FLAC数值分析

以高西沟露天煤矿的西北边帮作为研究对象,运用FLAC3D数值模拟软件,经过数值计算得到边坡安全系数为1.57,其与工程类比法计算得到的数值差不多,知该数值分析方法不仅能快速、准确的算出边坡的稳定性系数,还能够形象的描绘边坡的滑移临界场,是一种有效的边坡稳定性分析的方法。     

孔隙水对深部巷道稳定性影响研究

随着经济的飞速发展,对资源的需求量越来越大,长期大强度的开采导致浅部的矿产资源已日渐枯竭,矿产资源的开采向深部转移,巷道的稳定性将受到高地应力和高孔隙水压力等深部恶劣环境的影响。因此本文运用岩体力学理论和有限差分软件FLAC3D,考虑流-固耦合的情况下,对高地应力下孔隙水压力的巷道的变形和稳定性进行了理论分析和数值模拟,得到孔隙水的存在使巷道变形增大,巷道的稳定性减弱。