Are All Individual Investors Created Equal? Evidence from Individual Investor Trading around Securities Litigation Events

2006 ◽  
Vol 2 (2) ◽  
pp. 123-150 ◽  
Author(s):  
Paul A. Griffin ◽  
Ning Zhu
2008 ◽  
Vol 83 (6) ◽  
pp. 1521-1550 ◽  
Author(s):  
David A. Hirshleifer ◽  
James N. Myers ◽  
Linda A. Myers ◽  
Siew Hong Teoh

ABSTRACT: This study tests whether nai¨ve trading by individual investors, or some class of individual investors, causes post-earnings announcement drift (PEAD). Inconsistent with the individual trading hypothesis, individual investor trading fails to subsume any of the power of extreme earnings surprises to predict future abnormal returns. Moreover, individuals are significant net buyers after both negative and positive extreme earnings surprises, consistent with an attention effect, but not with their trades causing PEAD. Finally, we find no indication that trading by individuals explains the concentration of drift at subsequent earnings announcement dates.


2009 ◽  
Vol 45 (1) ◽  
pp. 169-198 ◽  
Author(s):  
Sophie Shive

AbstractI test whether social influence affects individual investors’ trading and stock returns. In each of the 20 most active stocks in Finland over 9 years, the number of owners in a municipality multiplied by the number of investors who do not own a stock, a measure of the rate of transmission of diseases and rumors through social contact, predicts individual investor trading. I control for known determinants of trade, including daily news, and show that competing explanations for the relation are unlikely. Socially motivated trades predict stock returns, and the effects are not reversed, suggesting that individuals share useful information. Individuals’ susceptibility to social influence has declined during the period, but the opportunities for social influence have increased.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ripsy Bondia ◽  
Pratap C. Biswal ◽  
Abinash Panda

PurposeCan something that drives our initial attention toward a stock have any implications on final decision to buy it? This paper empirically and statistically tests association, if any, between factors fostering attention toward a stock and rationales to buy it.Design/methodology/approachThis paper uses survey responses of individual investors involving multiple response categorical data. Association between attention fostering factors and rationales is tested using a modified first-order corrected Rao-Scott chi-square test statistic (to adjust for within-participant dependence among responses in case of multiple response categorical variables). Further, odds ratios and mosaic plots are used to determine the effect size of association.FindingsStrong association is seen between attention fostering factors and rationales to buy a stock. Further, strongest associations are seen in cases where origin is the same underlying influencing factor. Some of the most cited attention fostering factors and rationales in this research stem from familiarity bias and expert bias.Practical implicationsWhat starts as a trivial attention fostering factor, which may not even be recognized by majority investors, can go on to become one of the rationales for buying a stock. This can result in substantial financial implications for an individual investor. Investor education agencies and regulatory authorities can make investors cognizant of such association, which can help investors to improve and adjust their decision making accordingly.Originality/valueThe extant literature discusses factors/biases influencing buying decisions of individual investors. This research takes a step ahead by distinguishing these factors in terms of whether they play role of (1) fostering attention toward a stock or (2) of reasons for ultimately buying it. Such dissection of factors/biases, to the best of authors' knowledge, has not been done previously in any empirical and statistical analysis. The paper uses multiple response categorical data and applies a modified first-order corrected Rao-Scott chi-square statistic to test association. Application of the above-mentioned test statistic has not been done previously in context of individual investor decision-making.


Author(s):  
M. Kersch ◽  
G. Schmidt

Trading decisions in financial markets can be supported by the use of trading algorithms. To evaluate trading algorithms and to generate orders to be executed on the stock exchange trading systems are used. In this chapter, we define the individual investors’ requirements on a trading system, and analyze 17 trading systems from an individual investor’s point of view. The results of our study point out that the best alternative for an individual investor is not one single trading system, but a combination of two different classes of trading systems.


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