Individual Investor Trading Around Earnings Announcements


Book Description

This paper studies whether individual investors have information advantage before earnings announcements on an emerging market using a unique data set of TWSE. Consistent with existing research on American market, it is surprising that pre-event individual investor trading is also positively correlated with stock returns on and after earnings announcements dates in Taiwan. However, the sign of correlation between individual investor trading and stock return around earnings announcements shows weak evidence of noise trading rather than information advantage, which is opposite to that of American stock market.







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 Investors and Corporate Earnings


Book Description

This dissertation comprises two papers on the trading of individual investors around earnings announcements: 1. This study examines the effect of earnings announcements on individual investors' trading decisions and their trading profits. Consistent with earnings news informing the trading decisions of individual investors, I find that earnings announcements are associated with significant increases in individual investor market participation, and that these increases persist even after controlling for the information in prices. Moreover, and in contrast to the conventional wisdom that disclosure benefits unsophisticated investors at the expense of more sophisticated investors, I find that individuals' trades around earnings announcements earn economically and statistically significant losses, and that these losses are significantly greater than the losses of non-announcement trades. Consistent with these losses resulting from inefficient information processing, I find the higher the information content of the earnings announcement the greater the loss, and that increased losses around earnings announcements are concentrated among those individual investors who are not classified as affluent or active traders. Given the limited information processing ability of individual investors, the results suggest a more nuanced view of the welfare effects of disclosure. 2. This study examines the effect of contrarian retail trades on the pricing of earnings information. Consistent with price pressure from contrarian retail trades delaying the adjustment of prices to earnings information, I find that the negative price drift accompanying bad news is largest when retail investors buy on bad news, and that the positive price drift accompanying good news is largest when retail investors sell on good news. These findings are consistent with the correlated trading of retail investors around earnings announcements causing a delayed price adjustment which manifests as drift.




Individual Investors' Trading Responses to Accounting Disclosures


Book Description

A large amount of prior research that aim at understanding how individual investors respond to accounting disclosures uses transaction sizes to differentiate between small/individual and large/institutional investors. Recent studies have found that certain institutions are heavily involved in small size transactions. The analysis of individual investor trading based on transaction sizes erroneously draws inferences related to the small size transactions of institutional investors instead of transactions of individual investors. I re-investigate several fundamental issues using a comprehensive dataset of individual investor trading on the NYSE. First, I find that for individual investors there is a high concentration of trading around the earnings announcements and that the concentration is significantly higher than what is seen for the overall market. This finding is inconsistent with Cready [Journal of Accounting Research, 1-27 (1988)] which interprets the increase of the mean transaction size during the announcement periods as evidence that large/institutional investors find earnings information relatively more valuable than small/individual investors. Second, I show that individual investors’ buying is more concentrated than their selling which supports Lee [Journal of Accounting and Economics, 15(2-3), 265-302 (1992)]’s finding that individual investors are particularly prone to buying during the earnings announcement periods. Third, I do not find a significant positive association between individual investor abnormal trading and the magnitude of seasonal random-walk forecast errors during the announcement periods. This is inconsistent with Bhattacharya [The Accounting Review, 76(2), 221-244, (2001)] which shows a positive association between abnormal small size transactions and the magnitude of random-walk forecast errors, and interprets the finding as evidence that individual investors rely on seasonal random-walk model to form earnings expectations. Fourth, my analysis finds no evidence of the negative relation between 10K complexity and individual investor trading activity documented in Miller [ The Accounting Review, 85(6), 2107-2143, (2010)].




Market Ambiguity and Individual Investor Information Demand


Book Description

The U.S. capital market is based on the efficient flow of information to all investors, not just the large, institutional investors that dominate today's markets. Investigating the flow of information to uninformed market participants, we examine whether ambiguity in the market leads to an increase in information demand by individual investors. Basing our hypotheses on the asset pricing model proposed by Mele and Sangiorgi (2015), which incorporates market ambiguity, we measure individual information demand using daily Google searches and measure market ambiguity using a metric based on the market trades of institutional investors. We find that individual investors increase their information demand during periods of greater market ambiguity. In particular, our results show that for random trading days, when there is higher market uncertainty, individual investors demand more information. We also provide evidence that information demand from individual investors spikes around earnings announcement days primarily when market uncertainty is highest. We fail to find evidence of increased demand for information around earnings announcements when there is lower ambiguity, i.e., low disagreement among institutional investors. These results collectively indicate that information demand by uninformed investors is influenced by market uncertainty as measured by the differential trading patterns of informed investors. Finally, we provide evidence that institutional investor disagreement reflected in sell pressure leads to more information demand from individual investors. Overall, these results suggest that the disagreement among institutional investors either represents uncertainty or contributes to the uncertainty related to a stock, leading to increased demand for information from individual investors.







Option Strategies for Earnings Announcements


Book Description

By trading on corporate earnings, investors can reliably profit in both up and down markets, while avoiding market risk for nearly the entire quarter. In this book, two leading traders and portfolio managers present specific, actionable techniques anyone can use to capture these sizable profits. Ping Zhou and John Shon have performed an unprecedented empirical analysis of thousands of stocks, reviewing tens of millions of data points associated with option prices, earnings announcement returns, and fundamentals. Their massive analysis has identified consistent opportunities associated with focusing on the magnitude of the market’s reaction to earnings, not its direction. Option Trading Set-Ups for Corporate Earnings News offers concrete guidance for improving the likelihood of making correct forecasts, and managing the risks of incorrect forecasts. It introduces several ways to exploit option trading opportunities around earnings news, discuss crucial issues that most retail investors haven’t considered, and explore aspects of earnings-related option trading that have never been empirically examined and documented before. For example, they identify hidden patterns and potential opportunities based on valuation, industry, volatility, analyst forecasts, seasonality, and trades that immediately follow earnings announcements. Simply put, trading on earnings reports offers immense profit opportunities, if you know how. This book provides incontrovertible facts and detailed strategies, not just theories and anecdotes!




Informed Trading Behavior of Institutions and Individuals Around Earnings Announcements


Book Description

This study constructs the institutional- and individual-based probability of informed trading (PIN) by adjusting Easley, Hvidkjaer and O'Hara (2002) and investigates the impact of the informed trading behaviors of institutions and individuals on the post-announcement drift around the earnings announcement. The differences between this study and the previous literatures lie in that the investor types of informed traders are distinguished as institutions and individuals. Besides, the trading date effect is considered to examine the informed trading behaviors. The findings show that the informed trading behaviors of institutions and individuals can be distinguished. If there are informed traders involves in the stocks, the cumulative abnormal returns after the earnings announcement may be higher than the other stocks with no informed traders. Some individuals may possess relevant information that may prompt them to trade prior to or after the earnings announcement. The findings of the study may contribute to the government regulations and portfolio selections.




Trading Volume Around Firm-Specific Announcements


Book Description

This study investigates the impact of timing of the release of firm-specific announcements on trading volume of individual and institutional investors. We use trading data in five-minute intervals to capture the immediate impact of announcements on the trading volume. We find that individual investors exhibit positive and significant abnormal volume prior to, issued capital announcements and after earnings announcements. However, institutions exhibit significant and positive abnormal volume prior to, and after earnings, periodic and issued capital announcements. Notably, both individual and institutional investors do not exhibit significant abnormal volume prior to, and after dividend announcements. Furthermore, individual (institutional) investors' buy (sell) volume is significantly higher than sell (buy) volume prior to, and after scheduled and unscheduled announcements. Our results suggest that timing of the release of firm-specific announcements influences investor trading volume.