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An Empirical Analysis of the Effects of Online Trading on Stock Price and Trading Volume Reactions to Earnings Announcements

An Empirical Analysis of the Effects of Online Trading on Stock Price and Trading Volume Reactions to Earnings Announcements
Author: Anwer S. Ahmed
Publisher:
Total Pages:
Release: 2005
Genre:
ISBN:

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This study provides evidence on the effects of online trading on stock price and trading volume reactions to quarterly earnings announcements. We test for differences in stock price and volume reactions to quarterly earnings announcements between a period with a significant amount of online trading (1996-1999) and a period without online trading (1992-1995). We conjecture that online trading has increased the proportion of naive investors in the market. We predict that this will result in (i) a decrease in the average precision of investor information prior to earnings announcements implying higher ERCs, (ii) an increase in differential interpretation of earnings leading to higher trading volume reactions that are unrelated to price change, and (iii) a decrease in differential prior precision leading to a decrease in the association between trading volume and absolute price change. We find evidence consistent with all three predictions. Our findings are relevant for assessing the validity of concerns about online trading expressed by regulators and the validity of theoretical models of trade with asymmetrically informed investors.


An Empirical Analysis of the Effects of Online Trading on Investor Reactions to Earnings Announcements

An Empirical Analysis of the Effects of Online Trading on Investor Reactions to Earnings Announcements
Author: Anwer S. Ahmed
Publisher:
Total Pages: 41
Release: 2002
Genre:
ISBN:

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This study provides evidence regarding the effects of online trading on stock market reactions to quarterly earnings announcements. We test for differences in stock price and volume reactions to quarterly earnings announcements between a period with a significant amount of online trading (1996-1999) and a period without online trading (1992-1995). We conjecture that online trading has increased the proportion of naive investors in the market. Based on noisy rational expectations models of trade, we predict that this will result in larger stock price and trading volume reactions to earnings announcements. We find strong evidence in support of these predictions. The stock price results suggest that the advent of online trading has decreased average prior precision and the trading volume results suggest that online trading has increased differential belief revisions around earnings announcements. An analysis of the relation between volume reactions and price reactions in both periods suggests that the increase in differential belief revisions is primarily due to an increase in the differential interpretation of earnings announcements in the online trading period. Our findings are relevant for assessing the validity of concerns about online trading expressed by regulators and the validity of theoretical models of trade with asymmetrically informed investors.


Investors' Trade Size and Trading Responses Around Earnings Announcements

Investors' Trade Size and Trading Responses Around Earnings Announcements
Author: Neil Bhattacharya
Publisher:
Total Pages:
Release: 2013
Genre:
ISBN:

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Prior research suggests that the earnings expectations of a segment of the market can be described by the seasonal random-walk model. Prior research also provides evidence that less wealthy and less informed investors tend to make smaller trades (small traders) than wealthier and better informed investors (large traders).I hypothesize that it is the earnings expectations of small traders that are associated with predictions from the seasonal random-walk model. By directly analyzing the trading activities of small and large traders, this study provides evidence that is largely consistent with the hypotheses.Specifically, small traders' trading response around earnings announcements is increasing in the magnitude of seasonal random-walk forecast errors even after controlling for absolute analyst forecast errors, contemporaneous price changes, and market-wide trading. Supplementary analysis reveals that this effect is largely confined to firms with relatively impoverished information environments (i.e., smaller firms and firms with little to moderate analyst following).


The Changing Behavior of Trading Volume Reactions to Earnings Announcements

The Changing Behavior of Trading Volume Reactions to Earnings Announcements
Author: Orie E. Barron
Publisher:
Total Pages: 53
Release: 2016
Genre:
ISBN:

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The increase in investor diversity over the last 35-40 years (ICI 2014) prompted us to revisit trading volume reactions to earnings announcements and how these reactions vary with firm size. This increase in investor diversity would likely lead to an increase in differences in the precision of pre-announcement information and potentially increase the importance of earnings announcements to resolve investor disagreement. We find that the nature of trading volume reactions to earnings announcements has fundamentally changed over the 35-year time period 1977-2011. There has been a dramatic increase in the magnitude and frequency of volume reactions to earnings announcements over this time period, and this effect is more pronounced in large firms where volume reactions were previously infrequent. The increase in large firms' trading volume reactions is so pronounced that the relation between volume reactions and firm size has turned positive in recent years, thereby reversing Bamber's (1986, 1987) previously documented negative relation. We provide intuition and empirical evidence that our results are attributable to the resolution of differential prior precision among an increasingly diverse set of investors following large firms.


International Bibliography Of Economics 2003

International Bibliography Of Economics 2003
Author: Compiled by the British Library of Political and Economic Science
Publisher: Psychology Press
Total Pages: 698
Release: 2004-12
Genre: Business & Economics
ISBN: 9780415354776

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First published in 1952, the International Bibliography of the Social Sciences (anthropology, economics, political science, and sociology) is well established as a major bibliographic reference for students, researchers and librarians in the social sciences worldwide. Key features * Authority: Rigorous standards are applied to make the IBSS the most authoritative selective bibliography ever produced. Articles and books are selected on merit by some of the world's most expert librarians and academics. * Breadth: today the IBSS covers over 2000 journals - more than any other comparable resource. The latest monograph publications are also included. * International Coverage: the IBSS reviews scholarship published in over 30 languages, including publications from Eastern Europe and the developing world. * User friendly organization: all non-English titles are word sections. Extensive author, subject and place name indexes are provided in both English and French.


Stock Price Reaction to Quarterly Earnings Announcements with Respect of Outlook Changes and Deviation to Consensus Forecast

Stock Price Reaction to Quarterly Earnings Announcements with Respect of Outlook Changes and Deviation to Consensus Forecast
Author: Benjamin Schmitt
Publisher:
Total Pages: 56
Release: 2015-06-12
Genre:
ISBN: 9783656972426

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Bachelor Thesis from the year 2008 in the subject Business economics - Investment and Finance, grade: 1.1, EBS European Business School gGmbH (Finance), language: English, abstract: Many authors have already studied about stock price reactions after earnings announcements yet, which is because of the importance of earnings announcements, in particular quarterly earnings announcements, for many investors. However, all major studies concerning this topic deal with long-term scenarios, the stock's price performance is measured for a time period of at least three quarters. Due to the fact that there are many investors, especially institutional investors such as hedge funds that trade stocks much more frequently, the existing studies are not relevant for them. This paper studies stock price reactions around quarterly earnings announcements for companies listed in Deutscher Aktienindex (DAX) or Midcap DAX (MDAX) with respect to changes of the company's full-year outlook and of earnings surprise regarding analyst consensus forecast within ten days before and after the announcement date. Hence, this paper aims to analyse short-term reaction to quarterly earnings announcements, which are of relevance for all investors, whose investment strategy is, at least partially, focussing on the short-term performance. The main target group of this analysis are therefore hedge funds and investors that run short-term strategies. Due to the fact that the widespread Event Study Methodology is focused on the long-term, it is irrelevant for this analysis.


Are Algorithmic Trades Informed? - An Empirical Analysis of Algorithmic Trading Around Earnings Announcements

Are Algorithmic Trades Informed? - An Empirical Analysis of Algorithmic Trading Around Earnings Announcements
Author: Alex Frino
Publisher:
Total Pages: 46
Release: 2015
Genre:
ISBN:

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This study examines the impact of corporate earnings announcements on trading activity and speed of price adjustment, analyzing algorithmic and non-algorithmic trades during the immediate period pre- and post- corporate earnings announcements. We confirm that algorithms react faster and more correctly to announcements than non-algorithmic traders. During the initial surge in trading activity in the first 90 seconds after the announcement, algorithms time their trades better than non-algorithmic traders, hence algorithms tend to be profitable, while non-algorithmic traders make losing trades over the same time period. During the pre announcement period, non-algorithmic volume imbalance leads algorithmic volume imbalance, however, in the post announcement period, the direction of the lead-lag relationship is exactly reversed. Our results suggest that as algorithms are the fastest traders, their trading accelerates the information incorporation process.