Digital Insiders and Informed Trading Before Earnings Announcements


Book Description

While it is widely acknowledged that companies face increasing cybersecurity risk stemming from hackers stealing customer information, a relatively unknown cybersecurity risk is from information leakage and subsequent trading by digital insiders - hackers who target corporations to obtain non-public corporate information for illegal trading. We use a firm-specific measure of cybersecurity risk mitigation based on textual analysis of 10-Ks to proxy for the organization's ability to reduce the probability of digital insider trading. We find that a larger share of new earnings information is incorporated into prices prior to earnings announcements for firms with low cybersecurity risk mitigation scores. We also find that pre-announcement trading by short sellers is more predictive of earnings surprises for firms with low cybersecurity risk mitigation. Further, on days closer to earnings announcements, firms with relatively low cybersecurity risk mitigation scores experience a larger increase in bid-ask spreads, particularly the adverse selection component. These results suggest that weak cybersecurity risk mitigation provides opportunities for acquisition of private information and that trading by privately informed traders is more likely in stocks of firms with higher exposure to cybercrimes.




Evidence of Informed Trading Prior to Earnings Announcements


Book Description

This study examines transactions in stocks during the thirty trading days prior to earnings announcements. Using two methodologies, we find evidence of informed trading for initiators of large transactions (presumably institutions) but not for initiators of small transactions (presumably individuals). Specifically, we find that, relative to a control period, initiators of large transactions tend to buy (sell) stocks prior to earnings announcements that exceed (fall short of) analyst forecasts. In addition, the fraction of total stock price movement that occurs on large transactions is substantially higher during the pre-announcement period than during the control period. Results of both tests suggest, contrary to previous research, that some large traders have and use superior private information prior to large earnings surprises.




Informed Trading Before Positive Vs. Negative Earnings Surprises


Book Description

This paper investigates whether institutional investors trade profitably around the announcements of positive or negative earnings surprises. Using Korean data over the period of 2001-2010, we find that information asymmetry is larger before negative earnings surprises (earnings shock) among investors and that the trading volume decreases only before earnings shock announcements due to the severe information asymmetry. We also find that institutions sell their stocks prior to earnings shock announcements whereas individual and foreign investors do not anticipate bad news. Finally, we find that institutional trade imbalance is positively related to the post-announcement abnormal returns of negative events. This study complements and extends prior literature on informed trading around earnings announcements by documenting evidence that domestic institutions exploit their superior information around particularly earnings shock announcements.




Informed Trading Before Positive Vs. Negative Earnings Surprises


Book Description

This paper investigates whether institutional investors trade profitably around earnings announcements. We argue that institutions have informational advantage before negative earnings surprises but not before positive earnings surprises since the positive news tend to leak to market before the event. Using unique Korean data over the period of 2001-2010, we find that trading volume decreases only before the negative event due to information asymmetry among investors. We also find that institutions sell the stock before the negative earnings surprises but individual investors do not anticipate the bad news, and that trade imbalance by the institutions is positively related to the announcement abnormal returns of the negative events. The evidence is consistent with our conjecture that the domestic institutions exploit their superior information around the negative earnings surprises. Our results also show that foreign investors do not have any informational advantage compared to local investors on the upcoming earnings news.




The Signal Quality of Earnings Announcements


Book Description

This study examines the revealed preference of informed traders to infer the extent to which earnings announcements are informative of subsequent stock price responses. From 2011 to 2015, a cartel of sophisticated traders illegally obtained early access to firm press releases prior to publication and traded over 1,000 earnings announcements. I study their constrained profit maximization: which earnings announcements they chose to trade vs. which ones they forwent trading. Consistent with theory, these traders targeted more liquid earnings announcements with larger subsequent stock price movement. Despite earning large profits overall, the informed traders enjoyed only mixed success in identifying the biggest profit opportunities. Controlling for liquidity differences, only 31% of their trades were in the most extreme announcement period return deciles. I model the informed traders' tradeoff between liquidity and expected returns. From this model, I recover an average signal-to-noise ratio of 0.4. I further explore two potential economic sources of this noise: (i) ambiguous market expectations of earnings announcements and (ii) heterogeneous interpretations of earnings information by the marginal investor. Empirically, I document that the informed traders avoided noisier earnings announcements as measured by both sources of noise.







So What Orders Do Informed Traders Use? Evidence from Quarterly Earnings Announcements


Book Description

This paper examines what orders informed traders use before quarterly earnings announcements. In particular, we investigate whether informed traders prefer median orders and market orders right before quarterly earnings announcements. Quarterly earnings announcements are anticipated events. Because informed traders expect their information advantage will disappear after the announcements, this information event provides a unique opportunity to test whether informed traders become more impatient and use more aggressive orders when the announcement is approaching. Our results show that when the information will be released soon but there is still enough time for the execution (from day -10 to day -6), informed investors use small orders and limit orders to trade stealthily and reduce price risk. Within five days right before the announcements, informed investors trade more aggressively. They start using large market orders to ensure the execution and high profits. Our findings that informed traders change their preference for order type and order size over time shed new light on the ongoing debate on the order submission strategies by informed traders.




Trading on Corporate Earnings News


Book Description

Profit from earnings announcements, by taking targeted, short-term option positions explicitly timed to exploit them! Based on rigorous research and huge data sets, this book identifies the specific earnings-announcement trades most likely to yield profits, and teaches how to make these trades—in plain English, with real examples! Trading on Corporate Earnings News is the first practical, hands-on guide to profiting from earnings announcements. Writing for investors and traders at all experience levels, the authors show how to take targeted, short-term option positions that are explicitly timed to exploit the information in companies’ quarterly earnings announcements. They first present powerful findings of cutting-edge studies that have examined market reactions to quarterly earnings announcements, regularities of earnings surprises, and option trading around corporate events. Drawing on enormous data sets, they identify the types of earnings-announcement trades most likely to yield profits, based on the predictable impacts of variables such as firm size, visibility, past performance, analyst coverage, forecast dispersion, volatility, and the impact of restructurings and acquisitions. Next, they provide real examples of individual stocks–and, in some cases, conduct large sample tests–to guide investors in taking advantage of these documented regularities. Finally, they discuss crucial nuances and pitfalls that can powerfully impact performance.




Individual Investor Trading and Return Patterns Around Earnings Announcements


Book Description

This paper documents evidence consistent with informed trading by individual investors around earnings announcements using a unique dataset of NYSE stocks. We show that intense aggregate individual investor buying (selling) predicts large positive (negative) abnormal returns on and after earnings announcement dates. We decompose the abnormal returns into a component that is attributed to risk-averse liquidity provision and a component that is attributed to private information or skill, and show that about half of the abnormal returns in the three months following the event can be attributed to private information. We also examine the behavior of individuals after the earnings announcement and find that they trade in the opposite direction to both pre-event returns (i.e., exhibit "contrarian" behavior) and the earnings surprise (i.e., exhibit "news-contrarian" behavior). The latter behavior, which could be consistent with profit-taking, has the potential to slow down the adjustment of prices to earnings news and contribute to the post-earnings announcement drift.