Are trading bans effective? Exchange regulation and corporate insider transactions around earnings announcements

There is considerable controversy on the role of corporate insider trading in the financial markets. However, there appears to be a consensus view that some form of regulation concerning their activities should be imposed. One such constraint involves a trading ban in periods when corporate insiders are expected to be advantaged vis-à-vis the information flow. This paper directly tests whether constraints of this kind are effective in curtailing insider activity through a study of the trading characteristics of UK company directors. The London Stock Exchange Model Code (1977) imposes a two-month close period prior to company earnings announcements. We find that although the close period affects the timing of director trades, it is unable to affect their performance or distribution. Directors consistently earn abnormal returns irrespective of the period in which they trade. They tend to buy after abnormally bad earnings news and sell after abnormally good earnings news. Moreover, there are systematic differences in the trading patterns of directors surrounding interim and final earnings announcements. It appears that many corporate insiders have private information and exploit this in their trading activities. As a result, one can conclude that trading bans do not impose significant opportunity costs on the trading of corporate insiders.     

Asymmetric wealth gains in joint ventures: Theory and evidence

I examine the causes of asymmetric wealth gains (instances where one partner gains and the other partner loses) and the extent of these gains in joint ventures. I argue that asymmetric gains arise as the common benefits created by the venture are offset by the negative wealth effects of resource appropriation for one parent. Using a sample of 412 joint ventures I find that in 42% of the ventures one parent gained and the other lost. In addition, I find that when the abnormal returns of parents within a venture were compared, firms that gained more from forming the venture experienced [−1,0] returns of +3.22% and firms that gained less experienced [−1,0] returns of −1.37%. Additional analyses showed that asymmetric wealth gains tended to occur in ventures where one parent had relatively high valued resources and the other parent had relatively lower valued resources thus suggesting that resource appropriation may be an important cause of this pattern of gains.     

Is there a viable alternative to ordinary least squares regression when security abnormal returns are the dependent variable?

Regression analysis is often used to estimate a linear relationship between security abnormal returns and firm-specific variables. If the abnormal returns are caused by a common event (i.e., there is “event clustering”) the error term of the cross-sectional regression will be heteroskedastic and correlated across observations. The size and power of alternative test statistics for the event clustering case has been evaluated under ideal conditions (Monte Carlo experiments using normally distributed synthetic security returns) by Chandra and Balachandran (J Finance 47:2055–2070, 1992) and Karafiath (J Financ Quant Anal 29(2):279–300, 1994). Harrington and Shrider (J Financ Quant Anal 42(1):229–256, 2007) evaluate cross-sectional regressions using actual (not simulated) stock returns only for the case of cross-sectional independence, i.e., in the absence of clustering. In order to evaluate the event clustering case, random samples of security returns are drawn from the data set provided by the Center for Research in Security Prices (CRSP) and the empirical distributions of alternative test statistics compared. These simulations include a comparison of OLS, WLS, GLS, two heteroskedastic-consistent estimators, and a bootstrap test for GLS. In addition, the Sefcik and Thompson (J Accounting Res 24(2):316–334, 1986) portfolio counterparts to OLS, WLS, and GLS, are evaluated. The main result from these simulations is none of the other estimator shows clear advantages over OLS or WLS. Researchers should be aware, however, that in these simulations the variance of the error term in the cross-sectional regression is unrelated to the explanatory variable.

The impact of IMF term loans on US bank creditors’ equity values: an event study of South Korea's case

This study investigates whether the IMF term loan announcements to South Korea in late November and early December 1997 significantly increased the implicit value of the U.S. bank loans and investments to South Korea and hence, the equity values of its U.S. bank creditors. Using both the market model and the SUR model, this paper examines the potential abnormal performance of a total of 230 U.S. banks during mid-November to early December 1997. The findings show that there was a statistically significant positive equity response to the international bank creditors during the major event announcements. Further, the evidence shows the existence of different pricing behavior of different groups: groups that were more exposed experienced a more positive equity-price response.     

The Market Evaluation of Information in Directors' Trades

The purpose of this paper is to examine the propensity, characteristics and performance of directors' trades. Consistent with prior research we show that on average, directors outperform the market. However, we also find that there exist a large number of trades which do not share these abnormal share price returns and consequently have little information content. This has important consequences for market participants who use director trading activity as a signal for their own trading strategies. Using different measures of directors' trades based on trade characteristics, we report that purchases by directors are more informative than sales. In addition, the number of directors trading within a twenty day window and the percentage of the directors' holding that is being traded are both important factors in the abnormal share price performance following the trade.     

Insightful Insiders? Insider Trading and Stock Return around Debt Covenant Violation Disclosures

This study asks whether insider trading associates with an information advantage around first‐time debt covenant violation disclosures in SEC filings, which potentially results from early access to information about the debt covenant violation disclosure. We document two results. First, we find net insider selling up to 12 months before a debt covenant violation disclosure, which precedes investors' negative returns before disclosure; and net insider buying up to 12 months after disclosure, which precedes investors' positive returns after disclosure. Second, we show that net insider trading one to two months before and after the violation disclosure associates predictably with investors' short‐term reaction to the covenant violation announcement.     

Taming the blockchain beast? Regulatory implications for the cryptocurrency Market

This paper uses a unique dataset of 120 regulatory events from five classes to test the relevance of the regulatory framework for cryptocurrency value. Time-series market-wide estimates and panel estimates for 300 individual coins and tokens show statistically and economically significant impact of anti-money laundering and issuance regulation. Tighter regulation and more active role of government decrease cryptocurrency prices, evidencing that potentially lower risks and wider adoption commonly attributed to the establishment of the regulatory framework do not compensate for respective efficiency and consumer utility losses. The market is generally efficient in reflecting regulatory information in cryptocurrency prices.     

Cross-sectional Variation in Price Anticipation of Earnings

Estimates of the earnings response coefficient (ERC) can be improved by including leading returns in return-earnings models. This improvement in estimated ERC can be used to measure price anticipation of earnings. It is posited that this price anticipation is related to the information environment of a firm. Theories and prior empirical research pertaining to the information environment (e.g. Bhushan, 1989; Frankel et al., 1994) are used to identify three variables, breadth of trading, capital issues and volatility of returns, which potentially determine the extent of price anticipation of earnings. The empirical tests suggest that the tendency of prices to lead earnings is negatively related to thin trading and is positively related to the propensity for external financing and return volatility in the year immediately prior to that to which the anticipated earnings pertain.     

Measuring abnormal daily trading volume for samples of NYSE/ASE and NASDAQ securities using parametric and nonparametric test statistics

We extend prior research on the empirical properties of daily trading volume and methods to detect abnormal trading volume in two ways. We compare the performance of a nonparametric test statistic with the parametric test statistic used in prior research and we study samples of NASDAQ securities as well as samples of NYSE/ASE securities. Prior research has focused exclusively on NYSE securities. We find the nonparametric test statistic is more powerful in detecting abnormal trading volume than the parametric test statistic in both samples of NYSE/ASE and NASDAQ securities. We also document that abnormal trading volume will be detected more often in samples of NYSE/ASE securities compared to NASDAQ securities.     

Direct Evidence of Non-trading on the London Stock Exchange

The extent of non-trading is shown to be much greater in the UK than in the more heavily researched US equity markets. Over the period 1975 to 1995 we find that almost 44% of all stocks in our sample failed to trade on the last day of a given month, a figure which is significantly higher than for stocks in the US (see Foerster and Keim, 1993). In this paper we investigate the relationship between the non-trading of UK stocks and the autoregressive and seasonal behaviour of UK stock returns. In addition, we find that stocks are much more likely to be recorded as not having traded on the last day of the month in the period prior to April 1981 than after this date. We trace this result to a reporting requirement change on the London Stock Exchange and investigate whether the change has any real implications for systematic risk estimates over this period. We also find that alternative methods for calculating betas, in the presence of thin trading, are very sensitive to stock size and to non-trading.     

Nonparametric event study tests

This paper provides the first documentation of the power and specification of the generalized sign test, which is based on the percentage of positive abnormal returns in an estimation period. In simulations using daily stock return data, the generalized sign test is well specified with both exchange listed and NASDAQ stocks. A rank test is more powerful under ideal conditions. However, the rank test is more sensitive to increases in the length of the event window, to increases in return variance, and to thin trading. The generalized sign test is a viable alternative to the rank test under these conditions.     

The role of derivatives in hedge fund activism

Using a hand-collected sample of hedge fund activist engagements from 1994 to 2014, this study analysed the role of derivatives in the hedge fund activism. Evidence shows abnormal returns of targets of hedge fund activists who did not use derivatives exceeded the abnormal returns of targets of hedge fund activists who employed derivatives around the activist engagement disclosure period. We also find that idiosyncratic volatility of the targets of hedge fund activists who did not use derivatives was more reduced than that of the targets of hedge fund activists who used derivatives. Finally, the probability of takeovers increases for hedge fund activists who did not use derivatives.     

An Adjustment Procedure for Predicting Betas When Thin Trading is Present: Canadian Evidence

We have incorporated effects of the process that generates true betas for TSE stocks, as well as thin trading effects, into the beta adjustment model. We note the Blume and Dimson and Marsh beta adjustment techniques aim at eliminating beta forecast error through regression tendency bias. Effects of other sources of forecast error have been ignored. We show the process generating security betas affects both cross-sectional correlation coefficient and order bias, while thin trading affects only cross-sectional correlation coefficient. We demonstrate that when OLS beta estimates are used to forecast their future risk levels, order bias accounts for 86% of forecast error, while thin trading effects account for 14% of forecast error. A beta regression tendency model which properly accounts for effects of cross-sectional correlation (which is a function of thin trading) and order bias completely abates forecast error. Our results have implications for the use of correlation coefficient to measure stability of betas across time, for beta adjustment models proposed in the literature, and for event study methodologies that rely on prediction errors.