Pound wise and penny foolish? OTC stock investor behavior

2014 ◽  
Vol 6 (1) ◽  
pp. 2-25 ◽  
Author(s):  
John R. Nofsinger ◽  
Abhishek Varma
Keyword(s):  
Private Information ◽  
Sensation Seeking ◽  
Investor Behavior ◽  
Bulletin Board ◽  
Individual Investor ◽  
Trading Behavior ◽  
Over The Counter ◽  
Content Type ◽  
Penny Stocks ◽  
Different Characteristics

Purpose – The purpose of this paper is to explore some commonly held beliefs about individuals investing in over-the-counter (OTC) stocks (those traded on Over-the-counter Bulletin Board (OTCBB) and Pink Sheets), a fairly pervasive activity. The authors frame the analysis within the context of direct gambling, aspirational preferences in behavioral portfolios, and private information. Design/methodology/approach – Contrary to popular perceptions, the modeling of the deliberate act of buying OTC stocks at a discount brokerage house finds that unlike the typical lottery buyers/gamblers, OTC investors are older, wealthier, more experienced at investing, and display greater portfolio diversification than their non-OTC investing counterparts. Findings – Behavioral portfolio investors (Shefrin and Statman, 2000) invest their money in layers, each of which corresponds to an aspiration or goal. Consistent with sensation seeking and aspirations in behavioral portfolios, OTC investors also display higher trading activity. Penny stocks seem to have different characteristics and trading behavior than other OTC stocks priced over one dollar. Irrespective of the price of OTC stocks, the authors find little evidence of information content in OTC trades. Originality/value – The paper provides insight into individual investor decision making by empirically exploring the demographic and portfolio characteristics of individuals trading in OTC stocks.

New tool for stock investment risk management

2019 ◽  
Vol 120 (2) ◽  
pp. 388-405
Author(s):  
Yi Sun ◽  
Quan Jin ◽  
Qing Cheng ◽  
Kun Guo
Keyword(s):  
Risk Management ◽  
Stock Price ◽  
Price Change ◽  
Machine Learning Algorithms ◽  
Investor Behavior ◽  
Investment Risk ◽  
Individual Investor ◽  
Stock Selection ◽  
Content Type ◽  
Stock Investment

Purpose The purpose of this paper is to propose a new tool for stock investment risk management through studying stocks with what kind of characteristics can be predicted by individual investor behavior. Design/methodology/approach Based on comment data of individual stock from the Snowball, a thermal optimal path method is employed to analyze the lead–lag relationship between investor attention (IA) and the stock price. And machine learning algorithms, including SVM and BP neural network, are used to predict the prices of certain kind of stock. Findings It turns out that the lead–lag relationships between IA and the stock price change dynamically. Forecasting based on investor behavior is more accurate only when the IA of the stock is stably leading its price change most of the time. Research limitations/implications One limitation of this paper is that it studies China’s stock market only; however, different conclusions could be drawn for other financial markets or mature stock markets. Practical implications As for the implications, the new tool could improve the prediction accuracy of the model, thus have practical significance for stock selection and dynamic portfolio management. Originality/value This paper is one of the first few research works that introduce individual investor data into portfolio risk management. The new tool put forward in this study can capture the dynamic interplay between IA and stock price change, which help investors identify and control the risk of their portfolios.

Does uncertainty boost overconfidence? The case of financial analysts' forecasts

2014 ◽  
Vol 40 (3) ◽  
pp. 300-324 ◽  
Author(s):  
Véronique Bessière ◽  
Taoufik Elkemali
Keyword(s):  
Stock Returns ◽  
Private Information ◽  
High Tech ◽  
Cross Sectional ◽  
Forecast Dispersion ◽  
Content Type ◽  
The Public ◽  
Public Announcement ◽  
Before And After ◽  
Sectional Analysis

Purpose – This article aims to examine the link between uncertainty and analysts' reaction to earnings announcements for a sample of European firms during the period 1997-2007. In the same way as Daniel et al., the authors posit that overconfidence leads to an overreaction to private information followed by an underreaction when the information becomes public. Design/methodology/approach – In this study, the authors test analysts' overconfidence through the overreaction preceding a public announcement followed by an underreaction after the announcement. If overconfidence occurs, over- and underreactions should be, respectively, observed before and after the public announcement. If uncertainty boosts overconfidence, the authors predict that these two combined misreactions should be stronger when uncertainty is higher. Uncertainty is defined according to technology intensity, and separate two types of firms: high-tech or low-tech. The authors use a sample of European firms during the period 1997-2007. Findings – The results support the overconfidence hypothesis. The authors jointly observe the two phenomena of under- and overreaction. Overreaction occurs when the information has not yet been made public and disappears just after public release. The results also show that both effects are more important for the high-tech subsample. For robustness, the authors sort the sample using analyst forecast dispersion as a proxy for uncertainty and obtain similar results. The authors also document that the high-tech stocks crash in 2000-2001 moderated the overconfidence of analysts, which then strongly declined during the post-crash period. Originality/value – This study offers interesting insights in two ways. First, in the area of financial markets, it provides a test of a major over- and underreaction model and implements it to analysts' reactions through their revisions (versus investors' reactions through stock returns). Second, in a broader way, it deals with the link between uncertainty and biases. The results are consistent with the experimental evidence and extend it to a cross-sectional analysis that reinforces it as pointed out by Kumar.

Relationship amongst ResearchGate altmetric indicators and Scopus bibliometric indicators

2015 ◽  
Vol 116 (9/10) ◽  
pp. 564-577 ◽  
Author(s):  
RISHABH SHRIVASTAVA ◽  
Preeti Mahajan
Keyword(s):  
Sample Size ◽  
Correlation Coefficients ◽  
Strong Positive Correlation ◽  
Bibliometric Indicators ◽  
Pearson’S Correlation ◽  
Content Type ◽  
Positive Correlation ◽  
Pearson's Correlation ◽  
Different Characteristics ◽  
The Relationship

Purpose – The purpose of this paper is twofold. First, the study aims to investigate the relationship between the altmetric indicators from ResearchGate (RG) and the bibliometric indicators from the Scopus database. Second, the study seeks to examine the relationship amongst the RG altmetric indicators themselves. RG is a rich source of altmetric indicators such as Citations, RGScore, Impact Points, Profile Views, Publication Views, etc. Design/methodology/approach – For establishing whether RG metrics showed the same results as the established sources of metrics, Pearson’s correlation coefficients were calculated between the metrics provided by RG and the metrics obtained from Scopus. Pearson’s correlation coefficients were also calculated for the metrics provided by RG. The data were collected by visiting the profile pages of all the members who had an account in RG under the Department of Physics, Panjab University, Chandigarh (India). Findings – The study showed that most of the RG metrics showed strong positive correlation with the Scopus metrics, except for RGScore (RG) and Citations (Scopus), which showed moderate positive correlation. It was also found that the RG metrics showed moderate to strong positive correlation amongst each other. Research limitations/implications – The limitation of this study is that more and more scientists and researchers may join RG in the future, therefore the data may change. The study focuses on the members who had an account in RG under the Department of Physics, Panjab University, Chandigarh (India). Perhaps further studies can be conducted by increasing the sample size and by taking a different sample size having different characteristics. Originality/value – Being an emerging field, not much has been conducted in the area of altmetrics. Very few studies have been conducted on the reach of academic social networks like RG and their validity as sources of altmetric indicators like RGScore, Impact Points, etc. The findings offer insights to the question whether RG can be used as an alternative to traditional sources of bibliometric indicators, especially with reference to a rapidly developing country such as India.

Audit quality within adverse selection markets

2016 ◽  
Vol 24 (1) ◽  
pp. 2-18 ◽  
Author(s):  
Bharat Sarath
Keyword(s):  
Private Information ◽  
Stock Price ◽  
Audit Quality ◽  
Information Economics ◽  
Economic Market ◽  
Financial Reports ◽  
Content Type ◽  
General Terms ◽  
Audit Regulation ◽  
Short Run

Purpose – Auditing may be viewed as an arrangement for reducing inefficiencies arising from the fundamental market conflict between a seller who wants as high a price as possible and a buyer who wants to pay as low a price as possible. In more general terms, sellers prefer policies that boost the stock price in the short run whereas buyers would prefer the price to peak when they are ready to sell some time in the future. By framing audited financial reports within this context, the purpose of this paper is to provide some insights regarding both audit institutions and audit regulation. Design/methodology/approach – This paper relies on conceptual arguments and a simple analytical model. Findings – The basic findings are that a unique definition of audit quality is not compatible with the economics of a market where there are conflicts across traders as well a possibility that some traders hold superior information to others. Even an identification of quality with accuracy fails in this setting of conflict. The inference is that audit quality should be approached from a multi-dimensional perspective rather than a unique measure. Research limitations/implications – While the paper points out difficulties in constructing measures of audit quality extant in the literature, it does not provide any clear empirical suggestions for better measures. Originality/value – The paper brings back into focus issues from information economics that form the bedrock for the study of audited financial statements in equity markets. While the paper is partially a survey and synthesis of some of the latest empirical findings, it describes them within the context of a rational economic market where traders may possess private information. Within such a market, the paper outlines both the conflicts and the benefits inherent to the current institutional arrangements where auditors are paid by incumbent shareholders and overseen by regulators.

Investor protection, corporate governance and private information-based trading

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chun-Teck Lye ◽  
Chee-Wooi Hooy
Keyword(s):  
Corporate Governance ◽  
Emerging Markets ◽  
Private Information ◽  
Market Competition ◽  
Investor Protection ◽  
Civil Law ◽  
Securities Market ◽  
Market Manipulation ◽  
Content Type ◽  
Securities Laws

Purpose This study aims to examine the effects of investor protection (PROT), internal and external corporate governance (CG) on private information-based trading (PIBT). Design/methodology/approach This study uses a sample of 3,438 firms from 42 countries for the period 2002–2015 to examine the effects of the broad and specific measures of PROT, internal CG and external CG (product market competition and block ownership [BOWN]) on a more accurate measure of PIBT using regression analysis. Findings The results show that PROT and BOWN are effective in reducing PIBT. However, the specific measure of PROT (strength of PROT) is not significant in emerging markets and civil law countries. The internal CG is also significant but has a positive effect on PIBT. Research limitations/implications The results suggest that PROT law matters in the efforts to prevent PIBT. Policymakers and securities market regulators, particularly in emerging markets and civil law countries, should focus more on refining existing securities laws and enacting detailed securities rules that explicitly prevent specific market manipulation and PIBT. Originality/value This study provides evidence for the importance of specific and detailed securities rules in different market and legal environments. Furthermore, this study uses the segregated private information-based speculative trading component to accurately measure the PIBT.

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.

AI and privacy concerns: a smart meter case study

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jillian Carmody ◽  
Samir Shringarpure ◽  
Gerhard Van de Venter
Keyword(s):  
Private Information ◽  
Personal Information ◽  
Consumer Information ◽  
Data Sets ◽  
Smart Meter ◽  
Smart Meters ◽  
Content Type ◽  
Privacy Concerns ◽  
Privacy Legislation

Purpose The purpose of this paper is to demonstrate privacy concerns arising from the rapidly increasing advancements and use of artificial intelligence (AI) technology and the challenges of existing privacy regimes to ensure the on-going protection of an individual’s sensitive private information. The authors illustrate this through a case study of energy smart meters and suggest a novel combination of four solutions to strengthen privacy protection. Design/methodology/approach The authors illustrate how, through smart meter obtained energy data, home energy providers can use AI to reveal private consumer information such as households’ electrical appliances, their time and frequency of usage, including number and model of appliance. The authors show how this data can further be combined with other data to infer sensitive personal information such as lifestyle and household income due to advances in AI technologies. Findings The authors highlight data protection and privacy concerns which are not immediately obvious to consumers due to the capabilities of advanced AI technology and its ability to extract sensitive personal information when applied to large overlapping granular data sets. Social implications The authors question the adequacy of existing privacy legislation to protect sensitive inferred consumer data from AI-driven technology. To address this, the authors suggest alternative solutions. Originality/value The original value of this paper is that it illustrates new privacy issues brought about by advances in AI, failings in current privacy legislation and implementation and opens the dialog between stakeholders to protect vulnerable consumers.

scholarly journals Feedback Effects, Asymmetric Trading, and the Limits to Arbitrage

2015 ◽  
Vol 105 (12) ◽  
pp. 3766-3797 ◽  
Author(s):  
Alex Edmans ◽  
Itay Goldstein ◽  
Wei Jiang
Keyword(s):  
Private Information ◽  
Firm Value ◽  
Bad News ◽  
Good News ◽  
Asymmetric Effect ◽  
Trading Behavior ◽  
Feedback Effects ◽  
Limits To Arbitrage ◽  
Corporate Decisions ◽  
Fundamental Value

We analyze strategic speculators’ incentives to trade on information in a model where firm value is endogenous to trading, due to feedback from the financial market to corporate decisions. Trading reveals private information to managers and improves their real decisions, enhancing fundamental value. This feedback effect has an asymmetric effect on trading behavior: it increases (reduces) the profitability of buying (selling) on good (bad) news. This gives rise to an endogenous limit to arbitrage, whereby investors may refrain from trading on negative information. Thus, bad news is incorporated more slowly into prices than good news, potentially leading to overinvestment. (JEL D83, G12, G14)

Entrepreneurs’ network evolution – the relevance of cognitive social capital

2015 ◽  
Vol 21 (2) ◽  
pp. 197-223 ◽  
Author(s):  
Sara Jonsson
Keyword(s):  
Social Capital ◽  
Private Information ◽  
Three Dimensional ◽  
Network Evolution ◽  
Fashion Industry ◽  
Cognitive Dimension ◽  
Content Type ◽  
Start Up ◽  
The Creation ◽  
Cognitive Social Capital

Purpose – The purpose of this paper is to investigate entrepreneurs’ network evolution in the start-up phase. Design/methodology/approach – Based on the case studies of six fashion start-up firms, this study uses a three-dimensional perspective on social capital (structural, relational, cognitive) to investigate entrepreneurs’ network evolution (i.e. initiation of new relationships) in the start-up phase so as to acquire resources and support for firms’ goals. The study focuses particularly on the understudied cognitive dimension of social capital. The fashion industry provides a relevant research setting because it is characterised by changes in demand, which generate opportunities for entrepreneurship. Findings – The findings show that the display of cognitive attributes is important for the creation of structural social capital (the establishment of new relationships). The findings also indicate that relationships initiated based on the cognitive dimension have a high probability of developing into embedded relationships, thereby becoming high in the relational dimension and providing access to private information containing referrals to other actors. Thus, these relationships also promote the continued development of the structural dimension. Originality/value – The findings imply that the entrepreneurs’ sets of cognitive attributes constitute an important asset in the creation of social capital. They also point to the importance of signalling these values to potential resource holders. Relationships initiated through the display of cognitive attributes can provide resources without requiring immediate economic remuneration.

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