Individual investors and the Monday effect

2019 ◽  
Vol 45 (9) ◽  
pp. 1239-1252
Author(s):  
Bishal B.C. ◽  
Weiwei Wang ◽  
Ayfer Gurun ◽  
William Cready
Keyword(s):  
Stock Returns ◽  
Stock Prices ◽  
Individual Investors ◽  
Specific Information ◽  
Financial Advisors ◽  
Individual Investor ◽  
Trading Activity ◽  
Data Set ◽  
Content Type ◽  
Monday Effect

Purpose For this study, the authors document day-of-the-week trading patterns of individual investors using a unique data set of NYSE-listed firms and discuss their influence on the Monday effect. It is found that Monday stock returns are generally lower than those of other weekdays and, on average, negative. Unlike previous researchers, the authors use actual trading data for individual investors rather than proxies to measure individual investor activity, such as the percentage of odd-lot trading. The results demonstrate that the trading activity of individual investors on Mondays is lower than previously documented. This finding contradicts the long-held belief that individual investors are most active on Mondays. In addition, the authors find that individual investors’ trading activity during the week broadly follows corporate announcement patterns. The least amount of firm-specific information is released on Friday, followed by Monday, Tuesday, Thursday and Wednesday. Accordingly, individual investors trade the least number of shares on Friday, followed by Monday, Tuesday, Thursday and Wednesday, strengthening the argument that individual investors trade on attention-grabbing stocks. Taken together, the authors’ findings challenge those of previous studies that hold individual investors responsible for the Monday effect. The paper aims to discuss this issue. Design/methodology/approach The authors use actual trading data for individual investors rather than proxies to measure individual investor activity, such as the percentage of odd-lot trading, to study the existence of Monday effect in stock prices. Findings The results show that the trading activity of individual investors on Mondays is lower than previously documented. This finding contradicts the long-held belief that individual investors are most active on Mondays. In addition, the authors find that individual investors’ trading activity during the week broadly follows corporate announcement patterns. Research limitations/implications The authors find that individual investors’ trading activity during the week broadly follows corporate announcement patterns. The least amount of firm-specific information is released on Friday, followed by Monday. Accordingly, individual investors trade the least number of shares on Friday, followed by Monday, strengthening the argument that individual investors trade on attention-grabbing stocks. Taken together, the authors’ findings challenge those of previous studies that hold individual investors responsible for the Monday effect. Practical implications Financial advisors. Originality/value The authors find that individual investors’ trading activity during the week broadly follows corporate announcement patterns. The authors challenge the commonly hold view that individuals often make trading decisions during weekends and thus trade on Mondays, and find that the least amount of firm-specific information is released on Friday, followed by Monday. Accordingly, individual investors trade the least number of shares on Friday, followed by Monday. Taken together, the authors’ findings challenge those of previous studies that hold individual investors responsible for the Monday effect.

Noise traders and the rational investors: a comparison of the 1990s and the 2000s

2014 ◽  
Vol 41 (6) ◽  
pp. 849-862 ◽  
Author(s):  
Shady Kholdy ◽  
Ahmad Sohrabian
Keyword(s):  
Stock Returns ◽  
Stock Prices ◽  
Financial Time Series ◽  
A Priori ◽  
Impulse Response Function ◽  
Abnormal Returns ◽  
Individual Investors ◽  
Noise Traders ◽  
Content Type ◽  
Boom And Bust

Purpose – The purpose of this paper is to compare and contrast the effect of individual and institutional sentiments on the US stock returns during a prolonged bull phase of ten years in the 1990s compared to shorter boom and bust cycles of the 2000s. The study is focussed on a set of stocks that are prone to sentiments and speculations. Design/methodology/approach – To compare the dynamic interaction of individual and institutional sentiments and stock returns, the authors use the vector autoregression (VAR) approach. The VAR model has proven to be especially useful for describing the dynamic behavior of economic and financial time series because it does not impose a priori restriction on the structure of the system. Using impulse response function, the authors determine how stock returns respond over time to a shock in institutional and individual sentiments. Findings – The authors find that sentiments of individual investors can affect returns mostly when there is a prolonged upward trend in stock prices, while sentiments of institutional investors can impact the returns when stock market is more volatile. Originality/value – This paper compares the effect of noise traders and rational investors’ sentiment on stock returns during the persistent period of positive abnormal returns of the 1990s and the more volatile stock returns of the 2000s.

Mood and stock returns: evidence from Greece

2016 ◽  
Vol 43 (2) ◽  
pp. 242-258 ◽  
Author(s):  
Dimitrios Kourtidis ◽  
Željko Šević ◽  
Prodromos Chatzoglou
Keyword(s):  
Stock Returns ◽  
Stock Exchange ◽  
Negative Mood ◽  
Positive Mood ◽  
Individual Investors ◽  
Hedonic Tone ◽  
Data Set ◽  
Content Type ◽  
Athens Stock Exchange ◽  
And Performance

Purpose – The purpose of this paper is to examine the effect of investors’ emotional state (mood) on their trading behaviour and performance. Design/methodology/approach – A sample from a representative survey of 328 Greek individual investors has been used to empirically test the validity of the proposed associations. An iterative data collection process was followed, where individual investors had to complete a questionnaire every time they were trading in the Athens Stock Exchange, for a period of ten months. Exploratory factor analysis was first used to analyse the data set, followed by cluster analysis (to identify investor profiles based on differences in their mood). Findings – Two clusters have been identified. The first cluster profile includes investors with high score of positive mood (thus, high energetic arousal and hedonic tone, low tense arousal and anger frustration), while the second profile consists of investors with negative mood (low energetic arousal and hedonic tone, high tense arousal and anger frustration). The comparison between the two profiles has shown that investors with positive mood achieve higher stock returns than investors with negative mood. Originality/value – To the best of the authors’ knowledge there is no other similar study.

Local clientele: geography and comovement of stock returns

2018 ◽  
Vol 10 (3) ◽  
pp. 231-251 ◽  
Author(s):  
Vahap Uysal ◽  
Seth Hoelscher
Keyword(s):  
Stock Returns ◽  
Stock Prices ◽  
Spillover Effects ◽  
Metropolitan Statistical Area ◽  
Individual Investor ◽  
Investor Attention ◽  
Market Reactions ◽  
Content Type ◽  
The Impact ◽  
Local Firms

Purpose Local investors have the ability to impact the stock prices and returns of local firms. However, the impact of news made by a firm on local investors and neighboring companies is absent from the academic literature. The purpose of this paper is to fill that void and examine how a local investor clientele affects the stock market reactions of firms located within the same geographic proximity as a news-generating firm. Design/methodology/approach After accounting for firm, industry, and geographic characteristics, this study examines how a firm’s dividend initiation announcement (positive news) influences stock prices of seemingly unrelated firms within the same metropolitan statistical area (MSA). Findings Dividend-paying firms located in areas with a higher percentage of dividend clientele experience a positive comovement reaction when a seemingly unrelated firm within the same MSA announces a dividend initiation. The positive reactions are specifically for dividend-paying firms, while non-dividend payers exhibit no significant response. These results are robust to numerous regression methods and alternative explanations. Practical implications These findings are consistent with the positive-investor-attention hypothesis, suggesting positive spillover effects from news announcements for other local firms in the presence of individual investor clientele. Originality/value This is the first study to link how news generated by one firm can influence other geographically local firms, providing evidence on the impact of individual investor clientele on stock returns of local non-news firms.

An interactive query-based approach for summarizing scientific documents

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Farnoush Bayatmakou ◽  
Azadeh Mohebi ◽  
Abbas Ahmadi
Keyword(s):  
User Satisfaction ◽  
Information Needs ◽  
Specific Information ◽  
Information Need ◽  
Science Data ◽  
Data Set ◽  
Content Type ◽  
Interactive Query ◽  
Summarization System ◽  
Clear Idea

Purpose Query-based summarization approaches might not be able to provide summaries compatible with the user’s information need, as they mostly rely on a limited source of information, usually represented as a single query by the user. This issue becomes even more challenging when dealing with scientific documents, as they contain more specific subject-related terms, while the user may not be able to express his/her specific information need in a query with limited terms. This study aims to propose an interactive multi-document text summarization approach that generates an eligible summary that is more compatible with the user’s information need. This approach allows the user to interactively specify the composition of a multi-document summary. Design/methodology/approach This approach exploits the user’s opinion in two stages. The initial query is refined by user-selected keywords/keyphrases and complete sentences extracted from the set of retrieved documents. It is followed by a novel method for sentence expansion using the genetic algorithm, and ranking the final set of sentences using the maximal marginal relevance method. Basically, for implementation, the Web of Science data set in the artificial intelligence (AI) category is considered. Findings The proposed approach receives feedback from the user in terms of favorable keywords and sentences. The feedback eventually improves the summary as the end. To assess the performance of the proposed system, this paper has asked 45 users who were graduate students in the field of AI to fill out a questionnaire. The quality of the final summary has been also evaluated from the user’s perspective and information redundancy. It has been investigated that the proposed approach leads to higher degrees of user satisfaction compared to the ones with no or only one step of the interaction. Originality/value The interactive summarization approach goes beyond the initial user’s query, while it includes the user’s preferred keywords/keyphrases and sentences through a systematic interaction. With respect to these interactions, the system gives the user a more clear idea of the information he/she is looking for and consequently adjusting the final result to the ultimate information need. Such interaction allows the summarization system to achieve a comprehensive understanding of the user’s information needs while expanding context-based knowledge and guiding the user toward his/her information journey.

Information search in times of market uncertainty: an examination of aggregate and disaggregate uncertainty

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Marshall A. Geiger ◽  
Rajib Hasan ◽  
Abdullah Kumas ◽  
Joyce van der Laan Smith
Keyword(s):  
Information Search ◽  
Institutional Investors ◽  
Volume Index ◽  
Individual Investor ◽  
Market Uncertainty ◽  
Data Set ◽  
Current Time ◽  
Content Type ◽  
Information Demand ◽  
Google Search

PurposeThis study explores the association between individual investor information demand and two measures of market uncertainty – aggregate market uncertainty and disaggregate industry-specific market uncertainty. It extends the literature by being the first to empirically examine investor information demand and disaggregate market uncertainty.Design/methodology/approachThis paper constructs a measure of information search by using the Google Search Volume Index and computes measures of aggregate and disaggregate market uncertainty using institutional investors' trading data from Ancerno Ltd. The relation between market uncertainty, as measured by trading disagreements among institutional investors, and information search is analyzed using an OLS (Ordinary Least Squares) regression model.FindingsThis paper finds that individual investor information demand is significantly and positively correlated with aggregate market uncertainty but not associated with disaggregated industry uncertainty. The findings suggest that individual investors may not fully incorporate all relevant uncertainty information and that ambiguity-related market pricing anomalies may be more associated with disaggregate market uncertainty.Research limitations/implicationsThis study presents an examination of aggregate and disaggregate measures of market uncertainty and individual investor demand for information, shedding light on the efficiency of the market in incorporating information. A limitation of our study is that our data for market uncertainty is based on investor trading disagreement from Ancerno, Ltd. which is only available till 2011. However, we believe the implications are generalizable to the current time period.Practical implicationsThis study provides the first concurrent empirical assessment of investor information search and aggregate and disaggregate market uncertainty. Prior research has separately examined information demand in these two types of market uncertainty. Thus, this study provides information to investors regarding the importance of assessing disaggregate component measures of the market.Originality/valueThis paper is the first to empirically examine investor information search and disaggregate market uncertainty. It also employs a unique data set and method to determine disaggregate, and aggregate, market uncertainty.

Investigating association between factors fostering attention to a stock and rationales to buy it: an empirical analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ripsy Bondia ◽  
Pratap C. Biswal ◽  
Abinash Panda
Keyword(s):  
Decision Making ◽  
Categorical Data ◽  
Categorical Variables ◽  
Individual Investors ◽  
Multiple Response ◽  
Individual Investor ◽  
Test Statistic ◽  
Chi Square ◽  
Content Type ◽  
First Order

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.

Block trading, information asymmetry, and the informativeness of trading

2015 ◽  
Vol 5 (3) ◽  
pp. 215-235 ◽  
Author(s):  
Ningning Pan ◽  
Hongquan Zhu
Keyword(s):  
Information Asymmetry ◽  
High Frequency ◽  
Stock Return ◽  
High Frequency Data ◽  
Individual Investors ◽  
Specific Information ◽  
Frequency Data ◽  
Information Effect ◽  
Content Type ◽  
Two Measures

Purpose – The purpose of this paper is to investigate how block trading and asymmetric information contribute to the firm-specific information measured by the stock return synchronicity. Based on China stock market which is dominated by individual investors, this study focus on whether traders of block trading, which are usually institutional investors, are “information trader.” Design/methodology/approach – Based on the high frequency data, the paper constructs two measures of information asymmetry, intraday measure and inter-day measure. Then the paper constructs a multiple regression model and examine how block trading and information asymmetry contribute to the firm-specific information measured by the stock return synchronicity. Findings – The results show that: on the one hand, block trading transmits more firm-specific information, and can reduce the synchronicity; on the other hand, when the degree of information asymmetry is higher, block trading contains more firm-specific information and has a stronger effect on synchronicity. The effect of information asymmetry specifically displays as: block trading during the first half-hour of the trading day has a stronger effect on synchronicity; and block trading occurred in the days with publicly announced trading information has greater impact on synchronicity. Practical implications – The conclusions have important practical implications: for market regulators, monitoring for block trading can improve the recognition and prevention of insider trading; for individual investors, especially the risk aversion investors, recognition of intraday and inter-day information asymmetry is beneficial for them to avoid the risk of asymmetric information. Originality/value – First, the domestic and foreign research mostly concentrated impact of block trading on stock prices. However, reasons of stock price changes include the information effect and non-information effect, this paper selects stock return synchronicity as firm-specific information measure, and mainly focus on the information effect of block trading. Second, based on the high frequency data, the paper constructs two measures of information asymmetry, intraday measure and inter-day measure. Compared with general measure of information asymmetry, such as firm size, earnings quality, the two measures based on high frequency data are more precisely.

scholarly journals Stock returns, illiquidity and feedback trading

2020 ◽  
Vol 19 (2) ◽  
pp. 135-145
Author(s):  
Jing Chen ◽  
David G. McMillan
Keyword(s):  
Stock Returns ◽  
Positive Feedback ◽  
Stock Prices ◽  
Sovereign Debt ◽  
Negative Impact ◽  
Estimation Methods ◽  
Content Type ◽  
Study Results ◽  
European Markets ◽  
Feedback Trading

Purpose This study aims to examine the relation between illiquidity, feedback trading and stock returns for several European markets, using panel regression methods, during the financial and the sovereign debt crises. The authors’ interest here lies twofold. First, the authors seek to compare the results obtained here under crisis conditions with those in the existing literature. Second, and of greater importance, the authors wish to examine the interaction between liquidity and feedback trading and their effect on stock returns. Design/methodology/approach The authors jointly model both feedback trading and illiquidity, which are typically considered in isolation. The authors use panel estimation methods to examine the relations across the European markets as a whole. Findings The key results suggest that in common with the literature, illiquidity has a negative impact upon contemporaneous stock returns, while supportive evidence of positive feedback trading is reported. However, in contrast to the existing literature, lagged illiquidity is not a priced risk, while negative shocks do not lead to greater feedback trading behaviour. Regarding the interaction between illiquidity and feedback trading, the study results support the view that greater illiquidity is associated with stronger positive feedback. Originality/value The study results suggest that when price changes are more observable, due to low liquidity, then feedback trading increases. Therefore, during the crisis periods that afflicted European markets, the lower levels of liquidity prevalent led to an increase in feedback trading. Thus, negative liquidity shocks that led to a fall in stock prices were exacerbated by feedback trading.

Categorizing sentiment and its impact on REIT returns

2015 ◽  
Vol 41 (9) ◽  
pp. 958-973 ◽  
Author(s):  
Daniel Huerta ◽  
Dave O. Jackson ◽  
Thanh Ngo
Keyword(s):  
Investor Sentiment ◽  
Institutional Investor ◽  
Individual Investors ◽  
Individual Investor ◽  
Content Type ◽  
Portfolio Rebalancing ◽  
Multiple Sample ◽  
Security Pricing ◽  
And Performance ◽  
The Impact

Purpose – The purpose of this paper is to reexamine the impact of investor sentiment on real estate investment trust (REIT) returns using direct, survey-based measures of sentiment to categorize sentiment from institutional and individual investors. Design/methodology/approach – The authors provide a framework in which sentiment is classified into individual and institutional investor sentiment under the assumption that investors, depending on sophistication, react differently to the same set of information and will influence REIT prices differently. The authors employ a methodology that uses panel regression analyses and divides the sample of REITs into size and performance portfolios. Findings – The regression results suggest that institutional investor sentiment is positively and significantly related to REIT returns contemporaneously for multiple sample specifications. These results are consistent with high levels of institutional ownership in REITs. Results also suggest that individual investor sentiment only influences small capitalization and low-α portfolios. Originality/value – The findings provide more evidence on the influence of investor sentiment on security pricing even for highly regulated sectors such as the REIT industry. Investors may use changes in sentiment as signals for portfolio rebalancing and capital allocations.

An analysis of operating expense control within US multifamily properties

2017 ◽  
Vol 35 (1) ◽  
pp. 48-66 ◽  
Author(s):  
Andrew Carswell
Keyword(s):  
Explanatory Variable ◽  
Rental Housing ◽  
Positive Association ◽  
Individual Investors ◽  
Property Management ◽  
Property Market ◽  
Data Set ◽  
Content Type ◽  
Operating Income ◽  
The Usa

Purpose The purpose of this paper is to determine the effect that ownership and management structures have on ability to control operating expenses. For individual investors, intensity of management experience is also explored as a possible explanatory variable for operating expenses. For property management services that are contracted out, the level of the fee is investigated as a possible cause for movements in operating expenses as well. Finally, operating expenses are used as a possible explanatory variable for a property’s lease-up performance during the year. Design/methodology/approach The analysis consists of a series of regression models performed on data provided by the 2012 Rental Housing Finance Survey (RHFS) in the USA. The RHFS is a unique data set that covers a wide degree of information on multifamily properties. The RHFS represents 2,260 properties in total, and covers various aspects of the apartment industry, including financing and operational cost measures. Control variables used as independent variables include number of units, year of property acquisition, and age of building. Findings Individual ownership and self-management proved to be statistically significant drivers in driving down log operating expenses. Hours spent by individuals performing property management roles on their own properties had a slightly positive association with operating expenses. For professional managers, the fees devoted solely to the manager or management company had a highly significant and positive effect on other operating costs. Finally, when separating out the individual components of operating expenses, only two variables had significant effects on tenant lease-ups: management expenses (positive) and security expenses (negative). Research limitations/implications The data set is potentially biased toward those properties with less than 100 units, and thus it would be problematic to assume that these findings are generalizable to the population at large. There are also no geographic coding indicators within the RHFS data set, which eliminates the potential to control for various market factors and rural/urban differences. Practical implications The research provides an understanding of some of the basic factors behind increases in operating expenses, which ultimately has implications for performance benchmarks such as net operating income and property market value. Social implications The reasonable controlling of operating expenses ultimately has potentially positive implications for low- to moderate-income populations, who would ultimately experience lower rents as a result. Originality/value This research represents one of the first known uses of the RHFS database.

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