Behavioral Finance Research Research Articles

Behavioral biases in pension fund trustees’ decision making

PurposeBehavioral finance research has almost exclusively investigated the decision making of lay individuals, mostly ignoring more sophisticated institutional investors. The purpose of this paper is to better understand the relatively unexplored field of investment decisions made by pension fund trustees, an important subset of institutional investors, and identify future avenues of further exploration.Design/methodology/approachThis paper starts by setting out the landscape in which pension fund trustees operate and make their decisions, followed by a literature review of the extant behavioral finance research applicable to similar situations.FindingsDespite receiving training and accumulating experience in financial markets, these are limited and sparse; therefore, pension fund trustees are unlikely to be immune from behavioral biases. Trustees make decisions in groups, are heavily reliant on advice and make decisions on behalf of others. Research in those areas has uncovered many inefficiencies. It is still unknown how this specific context can affect the psychological effects on their decisions.Research limitations/implicationsGiven how much influence trustees’ decisions have on asset allocation and by extension in financial markets, this is a surprising state of affairs. Research in behavioral finance has had a marked influence on policy in the past and so we anticipate that exploring the decisions made within pension funds may have wide ramifications for the industry.Originality/valueAs far as the authors are aware, no behavioral research has empirically tested pension fund trustees’ decisions to investigate how the combination of group decisions, advice and surrogacy influence their decisions and, ultimately, the sustainability of our pensions.

A New Investor Sentiment Index Model and Its Application in Stock Price Prediction and Systematic Risk Estimation of Bull and Bear Market

Many studies in recent years have shown that investor sentiment affects investor decision-making, which in turn affects stock market volatility and the direction of stock market prices. Since behavioral finance researchers find that linear combinations of stock turnover and popularity indices can greatly reflect stock investor sentiment, this paper aims to construct a new investor sentiment index that can be reasonably applied to predict stock market risk by selecting rational factors. A new investor sentiment index model is first proposed by combining specific monthly new account ratio (SNIA), monthly turnover rate (TOR), popularity index AR, delayed yield (DY) and using principal component analysis approach. Secondly, the indicator is statistically tested. The results of the correlation analysis show that the investor sentiment index is positively correlated with the monthly rate of return, and the result of causal analysis reveals that the investor sentiment index is the Granger cause of the change in yield. Thirdly, a new method is designed to predict the stock price trend by using the presented investor sentiment index. Finally, based on VaR and CoVaR model the investor sentiment index can be utilized to forecast and estimate of systematic risk in the bull or bear market.

Impact of behavioral factors on investors’ financial decisions: case of the Egyptian stock market

PurposeThis paper aims to investigate the relationship between investors’ demographic characteristics (age, gender, education level and experience) and their investment decisions through behavioral factors (sentiment, overconfidence, overreaction and underreaction and herd behavior) as mediator variables in the Egyptian stock market.Design/methodology/approachThis paper collects data from a structured questionnaire survey carried out among 384 local Egyptian, foreign, institutional and individual investors. This paper used a partial multiple regression method to analyze the effect of investors’ demographic characteristics on investment decisions through behavioral factors as the mediator variable.FindingsInvestor sentiment, overreaction and underreaction, overconfidence and herd behavior significantly affect investment decisions. Also, age, gender and the level of education have significant positive effects on investment decisions by investors. Experience does not play a significant role in investment decisions, but as investors gain experience, they tend to overlook the emotional factors.Practical implicationsThe findings of this paper would help to understand common behavioral patterns of investors and indicate a path toward the growth of the Egyptian stock market.Originality/valueThere is a lack of research in behavioral finance covering Middle East and North African markets. This paper attempts to fulfill the gap by analyzing behavioral factors in the Egyptian market.

The Legal Framework for Financial Advertising: Curbing Behavioural Exploitation

Policy makers and behavioural finance scholars express growing concern that marketing practices by financial institutions exploit retail investors’ behavioural biases. Investor protection regulation should thus address these marketing practices and include mechanisms curbing behavioural exploitation. That raises the question whether the marketing communications regime of the new Markets in Financial Instruments Directive can live up to this demand. This article develops a regulatory model that integrates behavioural finance insights into the new marketing communications regime. It then determines how regulatory authorities can apply this model when they interpret and apply specific regulatory requirements. It demonstrates how a regulatory authority or a court can translate empirical behavioural finance research findings into legal arguments when assessing whether marketing practices can significantly distort a model investor’s decision-making process. The article further establishes that the detailed requirements imposed on investment firms by the new Markets in Financial Instruments Directive are necessary in order to protect investors from behavioural exploitation. Finally, the article submits policy proposals that aim to protect investors more effectively from behavioural exploitation.

Topic generation for Chinese stocks: a cognitively motivated topic modelingmethod using social media data

With the explosive growth of user-generated data in social media websites such as Twitter and Weibo, a lot of research has been conducted on exploring the prediction power of social media data in financial market and discussing the correlation between the public mood in social media and the stock market price movement. Our previous research has demonstrated that the topic-based public mood from Weibo can be used to predict the stock price movement in China. However, one of the most challenging problems in topic-based sentiment analysis is how to get the relevant topics about a stock. The relevant topics are also considered as concepts about a stock which can be used to build the ontology of stock market for semantic computing and behavioral finance research. In this paper, motivated by the basic level concept in cognitive psychology, we present a novel method using Latent Dirichlet Allocation (LDA) to generate topics about a stock based on the social media data. The experimental results show that the proposed method is e ective and better than other topic modeling methods. The topics generated by our method are more interpretable and could be used for topic-based sentiment analysis.

Behavioural biases among SME owners

People are not fully rational and their decisions suffer from errors and biases. Because behavioural finance research focuses on investor irrationality, additional attention should examine managerial decision-making. This study helps to fill this gap by addressing three objectives: (a) to identify whether owners of small and medium-sized enterprises (SMEs) in India are prone toward behavioural bias; (b) to assess the impact of these biases on their decision-making; and (c) to determine whether age, experience, education, and gender affect their propensity to exhibit behavioural biases. Using responses from 154 Indian SME owners, the study uses logistic regression to assess how demographic variables affect behavioural biases. The evidence shows that SME owners are prone to self-attribution, overconfidence, and loss aversion, but not anchoring. Differences exist in the working capital management decisions of owners prone to behavioural biases. Gender, age, and experience significantly affect the propensity to exhibit behavioural biases.

Interconexões entre finanças comportamentais e análise de redes sociais: uma investigação na literatura internacional

Tendo como referência a tomada de decisão, visualiza-se a importância das temáticas que envolvem finanças comportamentais, onde o indivíduo é analisado sob a ótica das heurísticas e vieses. Nesse sentido, a análise de redes sociais pode contribuir para ampliar os conhecimentos gerados por esta área, visto que considera as transações baseadas em rede. Para tanto, definiu-se como objetivo geral explorar os temas de finanças comportamentais e análise de redes sociais, identificando possíveis relações, com base em periódicos internacionais da área, durante o período de 2012 a 2016. Utilizou-se uma pesquisa bibliométrica em quatro periódicos internacionais relacionados a pesquisas em finanças comportamentais e análise de redes sociais. Como resultado, pode-se observar que, do total de artigos selecionados pelos termos de busca, vinte e cinco compuseram a amostra, sendo o Journal of Economic Psychology o periódico com mais publicações. Verifica-se que predominaram os artigos realizados de forma conjunta, com três autores, que em alguns casos estão vinculados a instituições e países distintos. Em âmbito do conteúdo dos artigos, visualiza-se temas relacionados a redes e questões sociais e comportamentais, sendo artigos empíricos, em sua maioria com a utilização de pesquisa survey e experimentos, visto tratar-se de aspectos associados a cognição.

Institutional investor behavioral biases: syntheses of theory and evidence

PurposeThis paper aims to review the theory and empirical evidence of institutional investor behavioral biases in the lenses of behavioral finance paradigm. It surveys the research specifically focusing on behavioral biases among institutional investors in investment management activities worldwide.Design/methodology/approachA literature survey is done to gather and synthesize evidence on behavioral biases of institutional investors.FindingsThe survey and analysis reveal the following findings. First, the theoretical underpinning of investors’ irrational behavior has been neglected in behavioral finance research. Second, the behavioral heuristics and biases are dynamic and complex. Third, understanding behavioral biases’ origin, causes and effects requires interdisciplinary perspectives from the fields of psychology, sociology and biology.Originality/valueThe analysis and alternative perspectives drawn in this paper provide new insights into the field of behavioral finance and aims to suggest researchers, practitioners and regulators on the next course of actions.

A Study on The Behavioural Aspects of Retail Investors for Investment Decision Making in Telangana State

Objective - Investment is the commitment of funds which have been saved from the current consumption with an expectation of favorable future returns. Investment behavior is concerned with choices made about the purchase of a significant number of securities for an individual or institutional account. Individual investment behavior is relatively a new area of research in behavioral finance. This study aims to identify the various behavioral patterns of retail investors and their investment decision making in the newly formed Telangana state of India. Methodology/Technique - Data were collected from a sample of 200 retail investors via a structured questionnaire. Factor analysis was then conducted to critically identify the behavioral patterns of the retail investors. Findings - The findings of this study indicate that the two behavioral factors of Heuristics and Prospect have significant impact on the investment decision making attitudes of the retail investors. Novelty - As a newly formed state in India, the Telangana state provides potential investment opportunities for retail as well as institutional investors. It is thus, highly imperative to explore how retail investors make investment decisions especially in the newly formed Telangana State in India Type of Paper: Empirical Keywords: Behavioral Factors; Behavioral Finance; Investment Behavior; Investment Decision Making; Retail Investor.

The different impacts of news-driven and self-initiated search volume on stock prices

Big data benefits both Internet finance and behavioral finance research; Internet search frequency on stocks has been widely used to measure investor attention. In this study, we divide the search volume into news-driven and self-initiated by the online media coverage collected from Baidu Index. In a sample of CSI 300 stocks from 2009 to 2013, we find that self-initiated (news-driven) search volume is more likely to generate buy (sell) pressure, and media coverage can negatively moderate the impact of search volume on stock prices, suggesting that distinguishing search environment for investors can help improve the measure for investor attention.

What Makes a Good Trader? On the Role of Intuition and Reflection on Trader Performance

Using simulations and experiments, we pinpoint two main drivers of trader performance: cognitive reflection and theory of mind. Both dimensions facilitate traders’ learning about asset valuation. Cognitive reflection helps traders use market signals to update their beliefs whereas theory of mind offers traders crucial hints on the quality of those signals. We show these skills to be complementary because traders benefit from understanding the quality of market signals only if they are capable of processing them. Cognitive reflection relates to previous Behavioral Finance research as it is the best predictor of a trader’s ability to avoid commonly-observed behavioral biases.

Development of Portfolio Theory: Pricing Deformations and Autonomous Self-regulation of the Financial Market

Scientists are looking for a single model of the financial markets. This model must take into account the whole complex of the identified factors and effects, including the achievements of behavioral economics. The scientific novelty of the proposals in this paper is combination the financial prerequisites of the neoclassical school and the achievements of the behavioral finance researchers in a single model. We propose to introduce the concept of the relative value of one percent of the possible positive earnings and the relative value of one percent of the possible negative income. This allows using the mechanism of implicit arbitrage. We also offer a way for the empirical evaluation of the parameters that we offer to make. The results can serve as a basis for the design and evaluation of financial instruments to identify and overcome the preconditions of pricing deformations in the context of modern portfolio theory and autonomous self-regulation of the financial market. DOI: 10.5901/mjss.2015.v6n6s7p237

The Rationality and Irrationality of Financing Green Start-Ups

Green start-ups contribute towards a transition to a more sustainable economy by developing sustainable and environmentally friendly innovation and bringing it to the market. Due to specific product/service characteristics, entrepreneurial motivation and company strategies that might differ from that of other start-ups, these companies might struggle even more than usual with access to finance in the early stages. This conceptual paper seeks to explain these challenges through the theoretical lenses of entrepreneurial finance and behavioural finance. While entrepreneurial finance theory contributes to a partial understanding of green start-up finance, behavioural finance is able to solve a remaining explanatory deficit produced by entrepreneurial finance theory. Although some behavioural finance theorists are suggesting that the current understanding of economic rationality underlying behavioural finance research is inadequate, most scholars have not yet challenged these assumptions, which constrict a comprehensive and realistic description of the reality of entrepreneurial finance in green start-ups. The aim of the paper is thus, first, to explore the specifics of entrepreneurial finance in green start-ups and, second, to demonstrate the need for a more up-to-date conception of rationality in behavioural finance theory in order to enable realistic empirical research in this field.

The factors forming investor’s failure: Is financial literacy a matter? Viewing test by cognitive mapping technique

AbstractThe objective of this paper is to apply cognitive map-related techniques to extract causal knowledge from a specific problem domain. This paper proposes to draw an average cognitive map in order to identify the failure factors of the Tunisian small investors. Our paper extends traditional and behavioral finance and previous research by proposing a new approach to building an average cognitive map for the explanation of small investors’ failure in the stock market.

Using Twitter to Predict the Stock Market

Behavioral finance researchers have shown that the stock market can be driven by emotions of market participants. In a number of recent studies mood levels have been extracted from Social Media applications in order to predict stock returns. The paper tries to replicate these findings by measuring the mood states on Twitter. The sample consists of roughly 100 million tweets that were published in Germany between January, 2011 and November, 2013. In a first analysis, a significant relationship between aggregate Twitter mood states and the stock market is not found. However, further analyses also consider mood contagion by integrating the number of Twitter followers into the analysis. The results show that it is necessary to take into account the spread of mood states among Internet users. Based on the results in the training period, a trading strategy for the German stock market is created. The portfolio increases by up to 36 % within a six-month period after the consideration of transaction costs.

The role of attention constraints for investor behavior and economic aggregates: what have we learnt so far?

Motivated by insights from psychology, a growing body of behavioral finance research highlights the importance of investors’ attention constraints. Collectively, this work suggests that time-series and cross-sectional variation in attention might not only materially affect the quality of market participants’ individual decision making, but eventually also matter for economic aggregates such as stock-level returns. While being notoriously difficult to measure, taking the role of human attention constraints into account might enable researchers to arrive at a better understanding of actual investor behavior as well as puzzling market phenomena, both of which are hard to reconcile with standard finance theory. Against this background, the goal of this paper is twofold. First, and with a focus on empirical work, it aims at providing a (necessarily selective) review, assessment, and synthesis of the research on limited investor attention. Second, it tries to identify gaps in the literature and to suggest fruitful directions for future research.

Using Lean Six Sigma to improve investment behavior

Purpose – This paper aims to use Lean Six Sigma (LSS) and consumption mapping concepts to develop a disciplined methodology for a self-directed investor so that adverse decision-making behaviors are avoided. Classical financial theories assume that individuals maximize expected utility by arriving at financial decisions in a rational manner. But, over time, investor performance has lagged behind corresponding market performance. Despite these results and research on their causes, investors continue to repeat systematic mistakes leading to suboptimal financial outcomes. Design/methodology/approach – Consumption maps are developed based on behavioral finance research that shows why investors make predictable and costly errors in their decision making. The authors show that the contemporary methodologies within LSS, used successfully in the manufacturing and service sectors, can be used to enforce rationality in investing. Findings – The approach proposed herein provides a new framework that researchers should be able to test in practice. By applying a structured, disciplined approach based on the Design-Measure-Analyze-Improve-Control (DMAIC) methodology of LSS, it is posited that the gap between financial theory and actual results can be bridged. Originality/value – Rather than hoping to avoid irrational behavior through self-awareness of behavioral biases, the DMAIC approach will standardize self-directed investor decision-making so that discipline is enforced.

Psychological barriers in oil futures markets

WTI and Brent futures are tested for the presence of psychological barriers around $10 price levels, applying a multiple hypothesis testing approach for statistical robustness. Psychological barriers are found to be present in Brent prices but not in WTI prices, which is argued to be due to the more prominent role that Brent plays as a global benchmark and, based on recent behavioural finance research, the greater complexity inherent in Brent fundamental value determination. Brent particularly displays evidence that when breaching a $10 barrier level from below with rising prices, the trend is for prices to fall on average subsequently. Similar behavioural-based patterns are evidenced at the $1 barrier level for the WTI–Brent spread. We show that psychological barriers only appear to influence prices in the pre-credit crisis period of 1990–2006, with such effects dissipating during the crisis and as markets reverted back to wider economy focused fundamentals. A range of reaction windows are applied with the main finding being that the trading potential around such psychological barrier levels is primarily in the immediate 1–5 days following a breach. The research contributes to the scant existing research on psychological influences on energy market traders, and suggests strong potential for further application of behavioural finance theories to improving understanding of energy markets price dynamics.

When Do Language Wrappers Matter? Market Reactions to Language Use in Earnings Announcements

While the linkage between firms’ announcement of corporate quarterly earnings and stakeholder reactions has been widely studied, much less is known about the possible impact of adding specific language to those earnings numbers. We draw on research in organization theory and behavioral finance to advance an original perspective on the nature of the financial market response to language use. Specifically, we analyze theoretically and empirically how financial market participants are likely to respond to the use of positive tone, causal attribution and time orientation in corporate quarterly earnings announcements. We highlight markets’ differential response to language relative to both organizational performance and overall market sentiment. We test and find general support for our predictions on the value of language using extensive data on 648 quarterly earnings announcements from NASDAQ- listed firms in bull and bear markets (1999 and 2002).

Situated cognition and narrative heuristic: evidence from retail investors and their brokers

In this paper, I discuss how a situated cognition perspective can reveal the socially constructed nature of seemingly psychological heuristics and errors in market actors’ judgements and decisions in financial markets. In doing so, I present a complementary approach to the heuristics and biases research in psychology and behavioural finance. More specifically, I draw on the narrative mode of knowing and explanation in real market settings as a framework to understand the content and the process of socially constructed knowledge in financial markets. Here, narratives of market actors and their underlying frames and causal schemas are assumed to function as a judgement heuristic in processing information flows. I then discuss an application of this approach to a sample of brokerage firms and investment advisers serving retail investors in the Istanbul Stock Exchange (ISE). My findings focus on a shared frame and the associated causal schema about the ISE and global financial markets. This observed interpretive model underpinned my interlocutors’ narrative judgements and forecasts about the ISE's movements and constituted a form of representativeness heuristic and anchoring.