This document summarizes a study that explores the relationship between rational mean-variance portfolio theory and behavioral portfolio theory from an investor's perspective. The study uses cognitive mapping interviews with 30 Tunisian investors to understand how they perceive key concepts from each theory. The cognitive maps are analyzed to identify interactions between concepts and "zones of communication" between the two theories. Preliminary results suggest investors use mean-variance concepts but are also influenced by behavioral biases and emotions. The study aims to provide a more realistic description of how investors make portfolio choices by combining elements of both rational and behavioral approaches.
The document discusses several articles related to security analysis and portfolio management. It summarizes Adam.Y.C.Lei & Huihua.li's experience using Bloomberg terminals in a finance course to teach students security analysis and portfolio management. It also summarizes Ali Asghary Karahroudy's analysis of security issues in cloud computing and a proposed file distribution model to address those issues. Finally, it briefly mentions several other articles related to composable security analysis, using chance constrained programming for security analysis and investment decisions, the definition of a project portfolio, criticisms of the Capital Asset Pricing Model, and estimating the value of security analysis and market timing ability.
MODELING THE AUTOREGRESSIVE CAPITAL ASSET PRICING MODEL FOR TOP 10 SELECTED...IAEME Publication
Systematic risk is the uncertainty inherent to the entire market or entire market segment and Unsystematic risk is the type of uncertainty that comes with the company or industry we invest. It can be reduced through diversification. The study generalized for selecting of non -linear capital asset pricing model for top securities in BSE and made an attempt to identify the marketable and non-marketable risk of investors of top companies. The analysis was conducted at different stages. They are Vector auto regression of systematic and unsystematic risk.
POSSIBILISTIC SHARPE RATIO BASED NOVICE PORTFOLIO SELECTION MODELScscpconf
This document summarizes a research paper that proposes new portfolio selection models using possibilistic Sharpe ratio to account for uncertainty in fuzzy environments. It defines possibilistic moments like mean, variance, skewness, and risk premium for fuzzy numbers. It then defines possibilistic Sharpe ratio as the ratio of possibilistic risk premium to standard deviation. New bi-objective and multi-objective portfolio models are presented that maximize possibilistic Sharpe ratio and skewness to allow for asymmetric returns. The models are solved using a genetic algorithm and tested on stock price data to demonstrate the approach.
This document discusses using fuzzy logic and genetic algorithms to optimize investment portfolio selection. It begins with an overview of traditional portfolio management approaches and their limitations. It then introduces using fuzzy logic to better represent uncertain information from financial markets. Trapezoidal fuzzy numbers are proposed to model variables like expected asset returns. Genetic algorithms are described as an optimization tool inspired by natural selection, and their application to the portfolio selection problem is discussed. The selection process would use fuzzy logic to rank investments based on financial indicators. The genetic algorithm would then operate on a population of portfolio solutions to maximize expected returns based on the fuzzy representations of the variables.
The investor indonesia behavior on stock investment decisionAlexander Decker
This document summarizes a research study that investigated how disposition effect, cognition, and accounting information influence individual investors' stock investment decisions in Indonesia. The study used a quasi-experimental design with 120 individual investors from Jakarta, Semarang, and Yogyakarta. The results showed that there is a disposition effect where investors sell winners faster than losers. Cognition tended toward risk taking and overconfidence after accounting information was provided. There was also an interaction between disposition effect, cognition, and accounting information that led to behavioral changes in individual investors.
This document provides tips for effective marketing campaigns, suggesting integrating different channels, demonstrating quick results, understanding the target audience, utilizing their spare time productively, leveraging celebrity endorsements, being first to market, proudly replicating successful ideas, and carefully listening to feedback.
This document discusses a research model examining factors that influence information sharing in inter-organizational relationships in supply chains. The model includes six constructs: relational benefits, relational proclivity, connectedness, power symmetry, dysfunctional conflict, and information sharing. An empirical study was conducted of 589 Taiwanese manufacturing firms to test hypotheses about the relationships between these constructs. The results suggest that relational benefits play a critical role in ensuring information sharing by reinforcing connectedness between supply chain members and mitigating dysfunctional conflicts, thus enhancing information sharing across the supply chain.
The document discusses several articles related to security analysis and portfolio management. It summarizes Adam.Y.C.Lei & Huihua.li's experience using Bloomberg terminals in a finance course to teach students security analysis and portfolio management. It also summarizes Ali Asghary Karahroudy's analysis of security issues in cloud computing and a proposed file distribution model to address those issues. Finally, it briefly mentions several other articles related to composable security analysis, using chance constrained programming for security analysis and investment decisions, the definition of a project portfolio, criticisms of the Capital Asset Pricing Model, and estimating the value of security analysis and market timing ability.
MODELING THE AUTOREGRESSIVE CAPITAL ASSET PRICING MODEL FOR TOP 10 SELECTED...IAEME Publication
Systematic risk is the uncertainty inherent to the entire market or entire market segment and Unsystematic risk is the type of uncertainty that comes with the company or industry we invest. It can be reduced through diversification. The study generalized for selecting of non -linear capital asset pricing model for top securities in BSE and made an attempt to identify the marketable and non-marketable risk of investors of top companies. The analysis was conducted at different stages. They are Vector auto regression of systematic and unsystematic risk.
POSSIBILISTIC SHARPE RATIO BASED NOVICE PORTFOLIO SELECTION MODELScscpconf
This document summarizes a research paper that proposes new portfolio selection models using possibilistic Sharpe ratio to account for uncertainty in fuzzy environments. It defines possibilistic moments like mean, variance, skewness, and risk premium for fuzzy numbers. It then defines possibilistic Sharpe ratio as the ratio of possibilistic risk premium to standard deviation. New bi-objective and multi-objective portfolio models are presented that maximize possibilistic Sharpe ratio and skewness to allow for asymmetric returns. The models are solved using a genetic algorithm and tested on stock price data to demonstrate the approach.
This document discusses using fuzzy logic and genetic algorithms to optimize investment portfolio selection. It begins with an overview of traditional portfolio management approaches and their limitations. It then introduces using fuzzy logic to better represent uncertain information from financial markets. Trapezoidal fuzzy numbers are proposed to model variables like expected asset returns. Genetic algorithms are described as an optimization tool inspired by natural selection, and their application to the portfolio selection problem is discussed. The selection process would use fuzzy logic to rank investments based on financial indicators. The genetic algorithm would then operate on a population of portfolio solutions to maximize expected returns based on the fuzzy representations of the variables.
The investor indonesia behavior on stock investment decisionAlexander Decker
This document summarizes a research study that investigated how disposition effect, cognition, and accounting information influence individual investors' stock investment decisions in Indonesia. The study used a quasi-experimental design with 120 individual investors from Jakarta, Semarang, and Yogyakarta. The results showed that there is a disposition effect where investors sell winners faster than losers. Cognition tended toward risk taking and overconfidence after accounting information was provided. There was also an interaction between disposition effect, cognition, and accounting information that led to behavioral changes in individual investors.
This document provides tips for effective marketing campaigns, suggesting integrating different channels, demonstrating quick results, understanding the target audience, utilizing their spare time productively, leveraging celebrity endorsements, being first to market, proudly replicating successful ideas, and carefully listening to feedback.
This document discusses a research model examining factors that influence information sharing in inter-organizational relationships in supply chains. The model includes six constructs: relational benefits, relational proclivity, connectedness, power symmetry, dysfunctional conflict, and information sharing. An empirical study was conducted of 589 Taiwanese manufacturing firms to test hypotheses about the relationships between these constructs. The results suggest that relational benefits play a critical role in ensuring information sharing by reinforcing connectedness between supply chain members and mitigating dysfunctional conflicts, thus enhancing information sharing across the supply chain.
Quality of ExperienceThe Good, The Bad,and The Ugly!Touradj Ebrahimi
The document discusses the evolution of quality of experience (QoE) in communication over time. It outlines some of the major evolutions and revolutions in communication technology. It also discusses the current state of QoE, including ongoing challenges in reliable QoE assessment methods, standardization efforts, and a lack of coordination in QoE research. Areas that require further work are identified as being content-dependent, context-dependent, and multi-modal QoE metrics.
The document outlines the steps to develop a business plan for an ISP, including: identifying the business objectives and market opportunity; estimating costs such as capital, recurrent, marketing, and staffing; modeling tariffs; and developing a financial model to project revenue and costs over multiple years. It provides examples of calculating infrastructure and transmission costs, developing tiered access pricing, and estimating demand and network capacity requirements to generate a profit and loss statement. The goal is to establish a tariff position and financial model that shows the business becoming profitable as the customer base and services grow over a 3-4 year period.
1) A small eurozone country exiting in a "hard money" way, by maintaining a fixed exchange rate with the euro for a period, could have limited impacts initially but risks encouraging others to follow suit.
2) The exit of a high-debt country like Spain or Italy would likely trigger deposit flights throughout other high-debt countries, testing the ECB's willingness to fully back banking systems and risking the end of the euro project.
3) While most politicians discuss exits as manageable, the design flaws and political tensions of the eurozone make fixes difficult, and unforeseen events could start a process leading to a full break-up with severe economic and legal consequences.
This document contains identifying information for four students including their photo, name, course of study, duration, address, and registration number. The information is organized into rows with labels for each category and includes details for four students pursuing a Bachelor of Engineering degree from 2013 to 2017.
Gamification is the use of game mechanics and design thinking to engage users and improve engagement, return on investment, data quality, and learning. It works by appealing to human psychology and motivating users through a sense of progression, validation, mitigation of failure, and promotion of growth. While extrinsic rewards like leaderboards and badges can boost engagement briefly, gamification is most effective when it focuses on intrinsic motivations by giving users a sense of autonomy, mastery, and purpose.
The document discusses foreign direct investment (FDI) and its trends and drivers from several perspectives:
1) It defines FDI and outlines some of its benefits for firms seeking new markets, distribution channels, cheaper production facilities and access to technology.
2) It discusses different theories that aim to explain FDI, including rational choice theory, behavioral theory and the internalization and OLI theories.
3) It examines factors that influence FDI decision-making processes within organizations, such as goals, resources, capabilities and uncertainty.
The document outlines 10 concepts for analyzing consumer markets and understanding consumer behavior from beginning to end. It discusses understanding the "whys" that define consumer buys, the factors that influence purchases including internal and external stimuli, and the multi-step buying process. It also covers how attitudes and beliefs shape buying decisions, consumers' post-purchase behaviors, and how they use and dispose of products over time. The overall goal is to understand consumers fully in order to best serve their needs.
The document describes a tri-partite model of computational knowledge. It proposes modeling human cognition using three modules that process information at different timescales and cognitive costs based on evolutionary features. Module I deals with unconscious knowledge like perception and attention. Module II involves conscious reasoning processes. Module III focuses on learning and development over various timescales. The model aims to quantitatively represent cognitive processes below rational reasoning to enable more human-like artificial intelligence.
Behaviour change massey presentation v3Michael Field
This is a conference presentation I did on behavioural change for the Massey University Sustainability Conference. Worked on the conference paper and presented with Joanne Tunna. Looks at how we drive positive behavioural change, including the common mistakes, cognitive dissonance etc.
This document discusses personality testing used in employee screening and selection. It examines the reasons companies use personality tests, concerns about their validity and reliability, and pitfalls of relying solely on test results to make hiring decisions. While tests can effectively screen out some unqualified candidates, well-qualified candidates may also be screened out if tests are the only criteria. The document argues that personality tests should be used to supplement interviews, not replace them, to achieve a better match between candidates and jobs.
This chapter discusses entrepreneurship and starting small businesses. It defines entrepreneurship as accepting the risk of starting and running a business. It profiles some notable entrepreneurs like É lruthè re Irè nè e du Pont de Nemours, David McConnell, George Eastman, and Jeff Bezos. The chapter also discusses why people take the entrepreneurial challenge, what it takes to be an entrepreneur, turning ideas into opportunities, benefits and downsides of home-based businesses, outsourcing work online, online businesses, and intrapreneurs working within companies. It concludes with statistics about small businesses in the US.
7.[54 59]the determinants of leverage of the listed-textile companies in indiaAlexander Decker
1) The document examines the determinants of leverage for 170 Indian textile companies over 2006-2010 using a fixed effects regression model with leverage ratio as the dependent variable.
2) Independent variables found to significantly influence leverage positively based on the results were firm size, non-debt tax shields, and asset tangibility, while growth and profitability significantly influenced leverage negatively.
3) These results were consistent with most previous theoretical and empirical research on the relationships between these firm-specific factors and leverage. The study adds to the existing literature on capital structure determinants.
Dr. Muhammad Yunus is a Bangladeshi economist and founder of Grameen Bank who pioneered microcredit and microfinance. He established Grameen Bank in 1983 to provide small loans known as microcredit to poor individuals, especially women, to allow them to start small businesses. Over 30 years, microcredit has spread worldwide helping countless families through Grameen Bank's banking facilities without requiring collateral. Dr. Yunus received many honors for his work, including the Nobel Peace Prize in 2006, for his efforts to create economic and social development.
This document summarizes the findings of market research conducted by Plantronics and Decision Analyst to understand communication trends among team knowledge workers. The research found that voice communication is still critical for business success and productivity, especially for urgent, complex, or sensitive discussions. While text-based communication has increased, it is preferred primarily for brief updates. Remote workers and those in distributed teams experience more communication issues. The research was featured in prominent media outlets and demonstrates how pure research can provide strategic insights to guide programs and thought leadership beyond immediate projects.
The document provides an overview of a presentation about understanding modern men and how they engage with television. It discusses busting myths about men and TV, establishing what influences men's lives and decisions, and extracting different segments of male viewers. The presentation aims to provide insights into men as television viewers in order to better target advertising and content.
The document provides guidance on creating an effective business plan for Janis Machala and Don Ferrel's startup company BigScreen. It discusses the purpose of a business plan for alignment, communication, and fundraising. Key aspects investors look for are described, like market size, management team, competitive advantages, and financial projections. The document emphasizes conducting in-depth competitive analysis and developing a sustainable competitive advantage. An overview of typical business plan format and sections is also provided.
11.[28 38]distribution of risk and return a statistical test of normality on ...Alexander Decker
This document summarizes a research study that examined the normal distribution of risk and return on the Dhaka Stock Exchange in Bangladesh. The study used statistical tests to analyze daily, weekly, and monthly returns calculated from three DSE indices from 2002 to 2010. The results found evidence of skewness and kurtosis in the returns, indicating they were not normally distributed and contradicting the assumption of random walk behavior required for an efficient market. Additionally, inconsistencies were found between daily and weekly risk and return, suggesting higher returns may be possible without higher risk. The study aims to contribute to evaluating market efficiency and the relationship between risk and return in the Bangladesh capital market.
An examination of the unit trust scheme mutual fund as a veritable vehicle of...Alexander Decker
This document examines unit trust/mutual funds as an investment vehicle in the Nigerian stock market. It begins with an abstract that provides background on Nigeria's economy and the growth of its capital markets in the 1990s and 2000s. It then discusses how many individual investors lacked skills and diversification during the global financial crisis, resulting in large losses. The document aims to examine unit trusts as a suitable investment option for small savers and less sophisticated investors. It finds there is a lack of awareness and poor patronage of unit trusts in Nigeria and that more education is needed. The document also notes that unit trusts could help mobilize funds and the economy would benefit from strengthened legal/accounting frameworks around these types of investments.
Why Behavioral Finance is Helpful for Investors to Decision Making Process?QUESTJOURNAL
ABSTRACT: Behavioral finance is the study of the influence of psychology on the behavior of financial practitioners and the subsequent effect on markets. It is of interest because it helps explain why and how markets might be inefficient.
Quality of ExperienceThe Good, The Bad,and The Ugly!Touradj Ebrahimi
The document discusses the evolution of quality of experience (QoE) in communication over time. It outlines some of the major evolutions and revolutions in communication technology. It also discusses the current state of QoE, including ongoing challenges in reliable QoE assessment methods, standardization efforts, and a lack of coordination in QoE research. Areas that require further work are identified as being content-dependent, context-dependent, and multi-modal QoE metrics.
The document outlines the steps to develop a business plan for an ISP, including: identifying the business objectives and market opportunity; estimating costs such as capital, recurrent, marketing, and staffing; modeling tariffs; and developing a financial model to project revenue and costs over multiple years. It provides examples of calculating infrastructure and transmission costs, developing tiered access pricing, and estimating demand and network capacity requirements to generate a profit and loss statement. The goal is to establish a tariff position and financial model that shows the business becoming profitable as the customer base and services grow over a 3-4 year period.
1) A small eurozone country exiting in a "hard money" way, by maintaining a fixed exchange rate with the euro for a period, could have limited impacts initially but risks encouraging others to follow suit.
2) The exit of a high-debt country like Spain or Italy would likely trigger deposit flights throughout other high-debt countries, testing the ECB's willingness to fully back banking systems and risking the end of the euro project.
3) While most politicians discuss exits as manageable, the design flaws and political tensions of the eurozone make fixes difficult, and unforeseen events could start a process leading to a full break-up with severe economic and legal consequences.
This document contains identifying information for four students including their photo, name, course of study, duration, address, and registration number. The information is organized into rows with labels for each category and includes details for four students pursuing a Bachelor of Engineering degree from 2013 to 2017.
Gamification is the use of game mechanics and design thinking to engage users and improve engagement, return on investment, data quality, and learning. It works by appealing to human psychology and motivating users through a sense of progression, validation, mitigation of failure, and promotion of growth. While extrinsic rewards like leaderboards and badges can boost engagement briefly, gamification is most effective when it focuses on intrinsic motivations by giving users a sense of autonomy, mastery, and purpose.
The document discusses foreign direct investment (FDI) and its trends and drivers from several perspectives:
1) It defines FDI and outlines some of its benefits for firms seeking new markets, distribution channels, cheaper production facilities and access to technology.
2) It discusses different theories that aim to explain FDI, including rational choice theory, behavioral theory and the internalization and OLI theories.
3) It examines factors that influence FDI decision-making processes within organizations, such as goals, resources, capabilities and uncertainty.
The document outlines 10 concepts for analyzing consumer markets and understanding consumer behavior from beginning to end. It discusses understanding the "whys" that define consumer buys, the factors that influence purchases including internal and external stimuli, and the multi-step buying process. It also covers how attitudes and beliefs shape buying decisions, consumers' post-purchase behaviors, and how they use and dispose of products over time. The overall goal is to understand consumers fully in order to best serve their needs.
The document describes a tri-partite model of computational knowledge. It proposes modeling human cognition using three modules that process information at different timescales and cognitive costs based on evolutionary features. Module I deals with unconscious knowledge like perception and attention. Module II involves conscious reasoning processes. Module III focuses on learning and development over various timescales. The model aims to quantitatively represent cognitive processes below rational reasoning to enable more human-like artificial intelligence.
Behaviour change massey presentation v3Michael Field
This is a conference presentation I did on behavioural change for the Massey University Sustainability Conference. Worked on the conference paper and presented with Joanne Tunna. Looks at how we drive positive behavioural change, including the common mistakes, cognitive dissonance etc.
This document discusses personality testing used in employee screening and selection. It examines the reasons companies use personality tests, concerns about their validity and reliability, and pitfalls of relying solely on test results to make hiring decisions. While tests can effectively screen out some unqualified candidates, well-qualified candidates may also be screened out if tests are the only criteria. The document argues that personality tests should be used to supplement interviews, not replace them, to achieve a better match between candidates and jobs.
This chapter discusses entrepreneurship and starting small businesses. It defines entrepreneurship as accepting the risk of starting and running a business. It profiles some notable entrepreneurs like É lruthè re Irè nè e du Pont de Nemours, David McConnell, George Eastman, and Jeff Bezos. The chapter also discusses why people take the entrepreneurial challenge, what it takes to be an entrepreneur, turning ideas into opportunities, benefits and downsides of home-based businesses, outsourcing work online, online businesses, and intrapreneurs working within companies. It concludes with statistics about small businesses in the US.
7.[54 59]the determinants of leverage of the listed-textile companies in indiaAlexander Decker
1) The document examines the determinants of leverage for 170 Indian textile companies over 2006-2010 using a fixed effects regression model with leverage ratio as the dependent variable.
2) Independent variables found to significantly influence leverage positively based on the results were firm size, non-debt tax shields, and asset tangibility, while growth and profitability significantly influenced leverage negatively.
3) These results were consistent with most previous theoretical and empirical research on the relationships between these firm-specific factors and leverage. The study adds to the existing literature on capital structure determinants.
Dr. Muhammad Yunus is a Bangladeshi economist and founder of Grameen Bank who pioneered microcredit and microfinance. He established Grameen Bank in 1983 to provide small loans known as microcredit to poor individuals, especially women, to allow them to start small businesses. Over 30 years, microcredit has spread worldwide helping countless families through Grameen Bank's banking facilities without requiring collateral. Dr. Yunus received many honors for his work, including the Nobel Peace Prize in 2006, for his efforts to create economic and social development.
This document summarizes the findings of market research conducted by Plantronics and Decision Analyst to understand communication trends among team knowledge workers. The research found that voice communication is still critical for business success and productivity, especially for urgent, complex, or sensitive discussions. While text-based communication has increased, it is preferred primarily for brief updates. Remote workers and those in distributed teams experience more communication issues. The research was featured in prominent media outlets and demonstrates how pure research can provide strategic insights to guide programs and thought leadership beyond immediate projects.
The document provides an overview of a presentation about understanding modern men and how they engage with television. It discusses busting myths about men and TV, establishing what influences men's lives and decisions, and extracting different segments of male viewers. The presentation aims to provide insights into men as television viewers in order to better target advertising and content.
The document provides guidance on creating an effective business plan for Janis Machala and Don Ferrel's startup company BigScreen. It discusses the purpose of a business plan for alignment, communication, and fundraising. Key aspects investors look for are described, like market size, management team, competitive advantages, and financial projections. The document emphasizes conducting in-depth competitive analysis and developing a sustainable competitive advantage. An overview of typical business plan format and sections is also provided.
11.[28 38]distribution of risk and return a statistical test of normality on ...Alexander Decker
This document summarizes a research study that examined the normal distribution of risk and return on the Dhaka Stock Exchange in Bangladesh. The study used statistical tests to analyze daily, weekly, and monthly returns calculated from three DSE indices from 2002 to 2010. The results found evidence of skewness and kurtosis in the returns, indicating they were not normally distributed and contradicting the assumption of random walk behavior required for an efficient market. Additionally, inconsistencies were found between daily and weekly risk and return, suggesting higher returns may be possible without higher risk. The study aims to contribute to evaluating market efficiency and the relationship between risk and return in the Bangladesh capital market.
An examination of the unit trust scheme mutual fund as a veritable vehicle of...Alexander Decker
This document examines unit trust/mutual funds as an investment vehicle in the Nigerian stock market. It begins with an abstract that provides background on Nigeria's economy and the growth of its capital markets in the 1990s and 2000s. It then discusses how many individual investors lacked skills and diversification during the global financial crisis, resulting in large losses. The document aims to examine unit trusts as a suitable investment option for small savers and less sophisticated investors. It finds there is a lack of awareness and poor patronage of unit trusts in Nigeria and that more education is needed. The document also notes that unit trusts could help mobilize funds and the economy would benefit from strengthened legal/accounting frameworks around these types of investments.
Why Behavioral Finance is Helpful for Investors to Decision Making Process?QUESTJOURNAL
ABSTRACT: Behavioral finance is the study of the influence of psychology on the behavior of financial practitioners and the subsequent effect on markets. It is of interest because it helps explain why and how markets might be inefficient.
Effect of Psychological Dispositions on Intuitive Forecasting: An Experiment...inventionjournals
International Journal of Business and Management Invention (IJBMI) is an international journal intended for professionals and researchers in all fields of Business and Management. IJBMI publishes research articles and reviews within the whole field Business and Management, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
This is a Behavioral Finance Lesson material which delivered by me for PhD students of Faculty of Business Administration in Karvina, Silesian University.
Behavioral Portfolio Theory
Behavioral portfolio theory(BPT), introduced by Shefrin and Statman (2000), provides an alternative to the assumption that the ultimate motivation for investors is the maximization of the value of their portfolios. It suggests that investors have varied aims and create an investment portfolio that meets a broad range of goals such as considering expected wealth, desire for security and potential, aspiration levels, and probabilities of achieving aspiration goals.
Traditional finance is based on three concepts: (1) rational behavior, (2) the capital asset pricing model, and (3) efficient market. While, the behavioral finance argue that psychological force would change decision maker’s mind make it not rational anymore, besides the market is not always efficient as well.
The BPT theory is not follow the same principle as Mean-Variance theory, Capital Asset Pricing Model, and Modern Portfolio Theory. However, authors developed BPT on the foundation of SP/A theory (Lopes, 1987) and prospect theory (Kahneman and Tversky, 1979) and closely related Safety-First Portfolio Theory.
In behavioral portfolio theory, authors build single account version of BPT -SA and multiple account version of BPT –MA. The theory is described as a single account version: BPT-SA, which is very closely related to the SP/A theory. In multiple account version (BPT-MA), investors can have fragmented portfolios, just as we observe among investors. They even propose in their initial article a Cobb–Douglas utility function that shows how money is allocated in the two mental accounts.
The BPT efficient frontiers and the mean-variance frontiers do not coincide. Mean- variance investors choose portfolios by considering mean and variance, which means average and risk. However, investors choose portfolios by considering their expected wealth, security level and potential gain, how to achieve goals. Behavioral portfolio theory is also the observation that investors view their portfolios not as a whole, as prescribed by mean-variance portfolio theory, but as distinct mental account layers in a pyramid of assets, where mental account layers are associated with goals and where attitudes toward risk vary across layers.
The CAPM is a model used to determine a theoretically appropriate required rate of return of an asset, to make decisions about adding assets to a well-diversifiedportfolio. The CAPM investors combine the market portfolio and the risk-free security. In contrast, the BPT investors resemble combine bond and lotter tickets.
Safety- First Portfolio Theory (Roy, 1952) is a risk management technique that allows an investor to select one portfolio rather than another based on the criterion that the probability of the portfolio's return falling below a minimum desired threshold is minimized. Roy was the first one who recognized a difference in financial decision-making that arose from varying behavioral sensitives according to the ...
Bridging the Gap between Psychology and Economics: The Role of Behavioral Fin...inventionjournals
This article is a descriptive presentation of how behavioral finance plays key role in providing insight into how individuals’ investment behavior typically deviates from traditional economic theories. The efficient market hypothesis (EMH) and capital asset pricing model (CAPM) theories have gained prominence in modern finance platform. The adequacy of these popular, rational-based behavior theories has however, remained skeptical among many scholars including Daniel Kahneman, Amos Tversky, and Richard H. Thaler. While the EMH and CAPM theories have contributed significantly to the investment world, some scholars contend the theories fail to fully explain certain inconsistent behaviors exhibited in the investment world. Behavioral finance is a new theory that attempts to fill the void between psychology and economics by providing a better understanding of investor behavior through the theories of psychology. Investment decisions are impacted by an array of irrational behavioral biases. The article identifies some finance and economic theory anomalies such as the January effect, equity premium puzzle, and others, which shift away from the traditional economic theories. Understanding these anomalies not only would assist individuals have a sense of how investors generally behave in the investment arena but also would help in efficient capital allocation.
This document provides an overview of the history and major works in the field of behavioural finance. It discusses early works from the late 19th/early 20th century exploring the psychology of markets. Major developments include prospect theory by Kahneman and Tversky in the 1970s, which found people overweight small probabilities and are loss averse. Their work on heuristics and biases also showed how psychology influences judgments. Behavioural concepts like mental accounting and overreaction have since helped explain apparent market inefficiencies. The field continues to incorporate psychological findings to better understand financial decision making.
Lecture 1 Introduction to Behavioral Finance [Autosaved].pptxMubashirAli440246
The document discusses the key assumptions and models of traditional finance, and the emergence of behavioral finance as an alternative approach. Specifically, it notes that traditional finance is based on the assumptions that investors are rational and markets are efficient. However, behavioral finance challenges this by incorporating insights from psychology about how cognitive biases and emotions can influence actual investor behavior and decision-making in irrational ways. As a result, behavioral finance questions some of the predictions of models like the efficient market hypothesis.
This document provides an overview of the background and literature related to utility theory and its application to financial decision making. It discusses classical utility models and their limitations, including issues with using logarithmic or expected utility functions to model situations with potential bankruptcy. It also reviews behavioral factors that influence perceptions of risk. The document outlines portfolio insurance as a risk management strategy and notes limitations in directly applying insurance principles to financial markets. It introduces the concept of utility from structured financial products that provide capital guarantees.
The document provides an introduction to behavioral finance, including:
1) Behavioral finance uses insights from psychology to understand puzzling stock market phenomena not explained by traditional finance which assumes rational markets and investors.
2) Some key objectives of behavioral finance are to review issues with standard finance, examine theories of both approaches, and identify investor personalities.
3) Major figures who helped develop behavioral finance include Daniel Kahneman and Amos Tversky who formulated prospect theory as an alternative to models assuming rational choices.
THE EMPIRICAL STUDY ON INVESTORS RISK PERCEPTION AND BEHAVIOUR OF EQUITY INVE...IAEME Publication
This document summarizes a study on investors' risk perception and behavior among equity investors in Tiruchirappalli District, India. It reviewed literature on behavioral finance and individual investment behavior. The study aimed to examine risk perception and understand factors influencing investment choices. A survey was conducted with 200 equity investors using questionnaires. Results found the majority preferred equities and evaluated performance monthly. Most were positive about financial future and invested between ages 50-59. Many lacked stock market experience but showed interest. Investors perceived high returns as most important and attitudes varied from diversification to viewing investing as gambling. About half engaged in investment activities. Risk tolerance differed and responses to market declines ranged from immediate liquidation to waiting for recovery.
Electronic copy available at httpssrn.comabstract=1629786.docxSALU18
Electronic copy available at: http://ssrn.com/abstract=1629786
1
Behavioral Portfolio Analysis of Individual Investors
1
Arvid O. I. Hoffmann
*
Maastricht University and Netspar
Hersh Shefrin
Santa Clara University
Joost M. E. Pennings
Maastricht University, Wageningen University, and University of Illinois at Urbana-Champaign
Abstract: Existing studies on individual investors’ decision-making often rely on observable socio-demographic
variables to proxy for underlying psychological processes that drive investment choices. Doing so implicitly ignores
the latent heterogeneity amongst investors in terms of their preferences and beliefs that form the underlying drivers
of their behavior. To gain a better understanding of the relations among individual investors’ decision-making, the
processes leading to these decisions, and investment performance, this paper analyzes how systematic differences in
investors’ investment objectives and strategies impact the portfolios they select and the returns they earn. Based on
recent findings from behavioral finance we develop hypotheses which are tested using a combination of transaction
and survey data involving a large sample of online brokerage clients. In line with our expectations, we find that
investors driven by objectives related to speculation have higher aspirations and turnover, take more risk, judge
themselves to be more advanced, and underperform relative to investors driven by the need to build a financial
buffer or save for retirement. Somewhat to our surprise, we find that investors who rely on fundamental analysis
have higher aspirations and turnover, take more risks, are more overconfident, and outperform investors who rely on
technical analysis. Our findings provide support for the behavioral approach to portfolio theory and shed new light
on the traditional approach to portfolio theory.
JEL Classification: G11, G24
Keywords: Behavioral Portfolio Theory, Investment Decisions, Investor Performance, Behavioral Finance
*
Corresponding author: Arvid O. I. Hoffmann, Maastricht University, School of Business and Economics,
Department of Finance, P.O. Box 616, 6200 MD, The Netherlands. Tel.: +31 43 38 84 602. E-mail:
[email protected]
1
The authors thank Jeroen Derwall and Meir Statman for thoughtful comments and suggestions on previous
versions of this paper. Any remaining errors are our own.
Electronic copy available at: http://ssrn.com/abstract=1629786
2
I. Introduction
The combination of increased self-responsibility for retirement and an aging population has led a
growing number of people to become accountable for their own financial futures. Considering
the significant impact of current investment choices on future lifestyles (Browning and Crossley,
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11.the portfolio choice in emergent markets a rational or a behavioral decision
1. European Journal of Business and Management www.iiste.org
ISSN 2222-1905 (Paper) ISSN 2222-2839 (Online)
Vol 4, No.2, 2012
The Portfolio Choice in Emergent Markets a Rational or a
Behavioral Decision: a Cognitive Answer
Ezzeddine Ben Mohamed1* Nizar Hachicha2 Abdelfatteh Bouri3
1. Faculty of Management, Unit of Research Corporate Finance and Financial Theory COFFIT, Sfax
University, PO box 1088, Sfax 3018, Tunisia
2. Faculty of Management, COFFIT ,Sfax University, PO box 1088, Sfax 3018, Tunisia
3. Faculty of Management, COFFIT ,Sfax University, PO box 1088, Sfax 3018, Tunisia
* E-mail of the corresponding author: benmohamed.ezzeddine@yahoo.fr
Abstract
The purpose of this study is to explore the relationship between the rational and the behavioral portfolio
theories, two theories that describes the decision making process on the domain of portfolio choice, under
investors’ perception. This will offer a more realistic answer that describes the investors’ decision on term
of portfolio choice. Our sample contains 30 Tunisian investors who trade at the Tunisian stock exchange
(BVMT). We introduce an approach based on cognitive mapping with a series of interviews. We combine
both concepts that belong to the mean-variance and the behavioral approach and we explore the interactions
between them. We introduce some new notions such as the zone of communication between the two cited
theories and the “variables of connection”. We demonstrate that investors use the mean-variance theory of
portfolio choice but they are affected by their cognitive biases and emotions when making their portfolio
choice decision.
Keywords: Mean-variance portfolio Choice, Behavioral Portfolio Choice, cognitive maps, areas of
communication, concepts of connection.
1. Introduction
One important bloc of the financial literature is the study of the wealth management and especially the
portfolio choice. How should investors constitute their portfolios? A practical answer was advanced by
Markowitz (1952, 1959). The portfolio choice is an arbitrage between the risk and the return of an asset.
The mean-variance portfolio approach assumes that investors are fully rational. They use a mean-variance
optimizer to maximize their utility function which has a concave form reflecting their risk-aversion.
Beyond the mean-variance framework, empirical and experimental researches argue that (Kahneman and
Tversky, 1979) investors are normal (Statman, 2005) and they are affected by their psychology when they
make decisions. This is the beginning of a new approach: the behavioral finance.
The main-contribution of the behavioral finance on the domain of portfolio management is with no doubt
the behavioral portfolio theory initiated by Shefrin and Statman (2000). A theory that derives from some
realistic hypothesis: Investors are normal (Statman, 2005) and they use an S-shaped utility function
(Kahneman and Tversky, 1979) that reflects their attitudes toward risk. Investors are also influenced by
their emotions (Lopes, 1987).
Researches in the financial theory are silent about the relationship between the rational mean-variance
theory of portfolio choice and the behavioral portfolio theory (Shefrin and Statman, 2000). There is no
specification concerning the existence or not of this relationship. In the case of the presence of such
relationships, we interrogate about the nature of this relationship: a relation of complementarities’ or
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2. European Journal of Business and Management www.iiste.org
ISSN 2222-1905 (Paper) ISSN 2222-2839 (Online)
Vol 4, No.2, 2012
substitutability?
There are two specific objectives of this study. Firstly, we intend to propose a methodology based on
cognitive mapping to detect the existence of a relationship between the rational mean-variance theory of
portfolio choice and the behavioral one. This will be obtained by the study of interactions between concepts
from these two theories and the detection of some area of communication between these theories.
The remainder of this paper is organized as follows. In the second section we provide a review of the
literature on the portfolio theories concept. The third deals with methodological details which include data
description and the analysis method. Section four discusses the empirical results. The fifth section generates
the empirical implications of our study. Finally, the sixth section offers concluding remarks and discusses
implications of our findings.
2. Literature review
In financial literature, the rational mean-variance theory of portfolio choice, as prescribed by Markowitz
(1952, 1959), is considered as the best approach for the construction and the management of assets. It
proposes some quantitative tools such as the mean and the standard deviation to respectively measure the
return and the risk of portfolio. The covariance is an important concept since it is very close to the
diversification concept.
In a rational framework of portfolio choice, investors act as if they are fully rational. At each time t,
investors try to choose stocks that maximize their utility function. This is will be an easier task when using
the mean-variance optimizer. However, Markowitz themselves do not follow this men-variance approach
(Statman, 2005).
The emergence of the behavioural finance should integrate, in the domain of portfolio management, new
dimensions such as investors’ psychology (Kahneman and Tversky, 1979, 1991) and emotions (Lopes,
1987). This is the centre of the Behavioral Portfolio Theory (Shefrin and Statman, 2000). This new theory
supposes the normality of investors. In their decision making, investors are affected by some psychological
biases
From a behavioural point of view, emotions such as hope and fear can affect investor’s wealth allocation.
This is by the creation of a safety aim excess or a potential aim excess. The Hope emotion may lead to an
excess of a “potential aim”. In this case, investor will be more attracted to invest on risky assets such as
stocks with the highest level of risk and so that can normally generate high return. Inversely, the Fear
emotion generates an excess of a “safety aim”. In term of portfolio choice, an investor who presents an
excess of a safety aim should react as it prescribed by Roy (1952). According to Roy (1952), safety first
investor trays to minimize the probability of ruin, it means the probability that his final wealth falls short of
a subsistence level s1.
In their descriptive theory, Shefrin and Statman (2000, 2003) introduce the mental accounting bias effect.
The mental accounting concept has been first used by Thalar (1980). He affirms that the mental accounting
attempts to describe the process whereby people code, categorize and evaluate economic outcome.
Investors use different mental account and each one has a specific aim. For example, an investor may
distinguish between the “safety aim” and the “potential aim”. In fact, the behavioural portfolio as initiated
by Shefrin and Statman (2000) has the form of a pyramid with two layers. The downside layer’s aim is the
protection from poverty. And it is a logic answer to the safety aim. The second one is the upside layer with
a potential aim’s. Each layer has a specific account and the covariance between layers is overlooked
(Shefrin and Statman, 2003).
A tentative reading and analysis for the cited theories of portfolio choice proves that each one have some
basic concepts that govern the portfolio choice’ decision. Table [1] summarizes the basic concepts for each
theory.
1
For more explanations see « The Behavioral Portfolio Theory », Shefrin and Statman (2000).
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3. European Journal of Business and Management www.iiste.org
ISSN 2222-1905 (Paper) ISSN 2222-2839 (Online)
Vol 4, No.2, 2012
The mean-variance theory of portfolio choice offered the first systematic treatment of a dilemma that each
investor faces: the conflicting objectives of high profit versus low risk (Steinbach C. 2001). Markowitz
proposes some quantitative tools to build and manage portfolios. The variance as a measure of risk and the
expected return as a measure of return help investors on their portfolio’s decision. The covariance between
assets and the diversification level are practical tools to manage investor’s portfolio. The literature revue
argues that these concepts are the basis of the rational mean-variance theory of portfolio choice (Markowitz
1952, 1959). Statman (2005) describes the mean-variance technique as “a practical tool” that aim to help
investors to overlap their cognitive bias.
An alternative theory to the mean-variance theory is the behavioral one (Shefrin and Statman, 2000). It is
on the basis of some psychological concepts. It is a theory that aims to integrate the role of behavioral
concepts. Namely, the “emotions”, “safety aim”, ”potential aim” and “mental accounting” can be
considered as the basic concepts in this new framework of portfolio choice. One important question is to
interrogate on the existence and the nature of the relationship between these two theories of portfolio choice.
Which theory can best describe the investors’ decision making in term of portfolio constitution and
management?
3. Materials and Methods
We use in this study the cognitive mapping technique. Downs and al. (1973) define the cognitive mapping as
“a process composed of a series of psychological transformations by which an individual acquires, codes,
stores, recalls, and decodes information about the relative locations and attributes of phenomena in their
every day spatial environment”. In more general terms, Arthur and Passini (1992) define cognitive map as
“an overall mental image or representation of the space and layout of a setting” this means that the cognitive
mapping is “the mental structuring process leading to the creation of a cognitive map”.
In his pioneering paper, Tolman (1948) argues that rats, like humans, have a mental representation of the
world he called a cognitive map. These maps hold detailed spatial information that individuals collect,
integrate and use while interacting with the environment. Tolman’s work has led to the modern psychological
definition of a cognitive map: an overall mental image or representation of the space and layout of a setting
(Arthur and Passini, 1992).
Axelrod (1976) introduces the cognitive maps as a formal way to model decision making in social-economic
and politic systems. According to Eden and Ackermann, 2004 the cognitive map is a representation of how
humans think about a particular issue this is guaranteed by analyzing, arranging the problems and graphically
mapping concepts that are interconnected. In addition, it identifies causes and effects and explains causal
links. The cognitive maps study perceptions about the world and the way they act to reach human desires
with- in their world (Bueno and Salmeron, 2009). It is a mental representation of a person’s environment,
relied upon during wayfinding (Sharlin et al 2009). It is attractive in the sense that it represents a set of
cause–effect relationships where the impact produced by the change of one or several elements over the
whole system is studied (Koulouriotis et al., 2003).
3.1 Sample selection and the interview process
Our sample consists of 30 Tunisian investors who trade or were traded at the Tunisian stock exchange
(BVMT). The limit size of our sample derives from the refusal of investors to participate. They explain their
refusal by the lack of time and they are seemed none interesting by the topic of the study. For each investor,
we realize an interview between 30 minutes to one hour. At the beginning of each interview, we present the
aim of our study. We use a semi-directive interview. Each investor was invited to talk about the 8 concepts
(variance, covariance, expected return, diversification, emotions, safety aim, potential aim and the mental
accounting). The discussion cover the meaning of these concepts from the investor’s point of view and
whether they affect or not their portfolio choice. After that, we invite each investor to draw his own cognitive
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ISSN 2222-1905 (Paper) ISSN 2222-2839 (Online)
Vol 4, No.2, 2012
map. A paper with the different cited concepts was distributed and he will link between concepts that can
have a relationship between them. He will indicate the orientation of each relationship. The intensity a
relationship between two concepts A and B can be week (with a value of 1), moderate (2) or strong (3).
During the interview process, we ask investors about any relationship that seemed illogically.
3.2 Analysis method
We concentrate on the interactions between concepts from the mean-variance theory of portfolio choice
(Markowitz 1952, 1959) and other from the behavioural portfolio theory of Shefrin and Statman (2000). In
our case the number of concepts is 4 from each theory. So, the adjacency matrix should contain 64
proximity’s relations.
In individual matrixes, the strength of the relationship between concepts may take four different values:
where i:=1,…,8 and j:=1,…,8.
In the special case, where we aim to detect the interactions between the mean-variance concepts and the
behavioural concepts of portfolio choice, each individual matrix contains two zones of communications.
We define the “zone of communications” as the special area in the adjacency matrix that detects the
influences of the mean-variance concepts (behavioural concepts) on the behavioural concepts
(mean-variance concepts). In the first area (The red matrix), aij represent the strength of the relationship
between i mean-variance concept on the behavioural concept j. In the second matrix, i denote behavioural
concept and j a mean-variance concept.
To delimit the investors’ perception globally, we follow Prigent and al 2008). We construct average maps
by calculating the arithmetic mean of the adjacency matrices. As a result, the intensity of the relationships
between two concepts may vary between 0 and 3. So that, we can write:
aij Є [0,3] where i := 1,…,8 , j: = 1,…,8 and i # j (1)
If the two theories are interrelated, in a conceptual form, then there will be some proximity’s relation aij
satisfying:
aij # 0 where i: 1,…,4 and j: 5,…,8. (The red matrix) (2)
aij # 0 where i: 5,…,8 and j: 1,…,4. (The blue matrix) (3)
Logically, if there will be some interactions between the mean-variance and the behavioural concepts of
portfolio choice, this means that these two theories are linked in the cognitive schema of an investor. For
example, if an investor indicates that “Emotions” influence the concept “variance”, this means that he is
oriented by his emotions in choosing the variance of his portfolio. In order to detect the cognitive relationship
between the two theories of portfolio choice, we identify some concepts that link the two theories. We
consider them as “connection variables”.
The cognitive relationship between two concepts may be absent, week, moderate or intense. And the strength
of the relations of proximities affects the quality of the relationship between the two considered theories. This
relationship is also an increasing function of the number of the proximities aij that satisfy conditions (1) and
(2).
The first zone of interactions (the red matrix), aims to detect influences exert by mean -variance concepts of
portfolio choice on others behavioural concepts. The second area of communication between the two
theories is represented by the blue colour. It aims to explore the impact of the behavioural concepts on the
mean-variance concepts of portfolio choice.
In order to calculate the intensity of the effect of each concept on others concepts, we calculate the weight of
each concept as bellow. We inspire from the graph theory the weight of each concept. In a first, step we
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5. European Journal of Business and Management www.iiste.org
ISSN 2222-1905 (Paper) ISSN 2222-2839 (Online)
Vol 4, No.2, 2012
calculate this weight according to the lines in each zone of communication. The formulation of weights is
described by the next two formulas:
The weight of the mean-variance concepts is calculated from the first zone (the red matrix) and it is the
summation of the each line of this matrix. Each mean-variance concept i has the next weight :
and (4)
The weight ) can serves as a measure of the intensity of influences exert by the mean-variance concept i
on all other behavioral concepts. The weight of the behavioural concepts is generated from the second area of
communication (the blue matrix). Each behavioural concept has the next weight :
and (5)
The weight ) can serve as a measure of the intensity of influences exerts by the behavioural concept i on
all other mean-variance concepts.
Logically, these weights reflect the capacity of each variable to link the two theories of portfolio choice in the
cognitive schema of investors from our sample. For more appreciation, we should integrate a new component
that measures the weight of influences exert by other variables on a specific concept i. we formulate these
weight as bellow:
The weight of influences received by the mean-variance concept j and exerted by the behavioural concepts is
calculated from the second area of communication (the blue matrix) as the summation of each column of this
matrix.
(6)
The weight of influences received by the behavioural concept j and exerted by the mean-variance concepts is
calculated from the first area of communication (the red matrix) as the summation of each column of this
matrix.
(7)
The utility of the calculation of these weight is to judge on the presence or not of a cognitive relationship
between the two theories. It reflects also the weight of each concept on each area of communication. The final
step in our analysis is the isolation of the most central concepts that govern the portfolio choice decision. This
objective may be attained by the calculation of a total weight for all the concepts in each area of
communication. We define the total weight of a Rational mean-variance concept i=j as :
(8)
While, total weight of a Behavioural concept i=j as as:
(9)
4. Results and discussions
Table [3] shows the different possible interactions between all considered concepts of the portfolio choice
theories. The adjacency matrix shows two areas of communication between the rational and the behavioural
concepts of portfolio choice. In a first step, we study the impact of the rational mean-variance concepts on
the behavioural concepts (this matrix is represented by the red colour). Then, we explore the influence of
the behavioural concepts on the rational one (this matrix is represented by the blue colour).
Our results show that the mean-variance concept “Diversification” affects all the behavioural concepts
(Emotions, Potential aim, Safety aim and Mental accounting). In their cognitions, the diversification is
closed to the safety aim.
In a cognitive map, a relationship between concept A and B means that A is the explanation of B or B is the
consequence of A (see Prigent and al, 2008). In our case, “Emotions” explain the level of the variance of
their portfolio (a51= 0.40). It affects also the technical concepts “Covariance” and “Expected Return”. This
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relationship goes into an intensity of 0.90. As it predicted by Statman (2005), “investors are normal” and
they are affected by their psychology when constructing and managing their portfolio.
The “Potential aim” and the “Safety aim” can govern the portfolio choice. Investors from our sample
consider that the existence of a safety aim or a potential aim affect the diversification level. However, these
two factors do not have the same weight in the cognitive universe of investors. The “safety first investors”
are more attracted by the diversification strategy. This is because they essay to conserve a subsistence level
as it described by “the safety first theory” of Roy (1952).
Our result corroborates the theoretical predictions of the behavioural portfolio theory (Shefrin and Statman,
2000). The most intense relationship in the first area of communications is between “Emotions” concept
and the “diversification” concept (a54= 1.80). This result may be explained by the low financial education of
Tunisian investors. Discussions with them during the interview let us concluding that there are more
familiar with the “Diversification” concept. The majority of interviewees know that “the diversification is
beneficial in the sense that it can reduce the risk of our portfolio”. This may also explain the week
relationships between the technical terms “variance”, “covariance” and “expected return”.
The mental accounting bias exerts an influence on the choice of the variance and the covariance. The
majority of interviewees affirm that they use they mental accounting when choosing between assets. For
example, if an investor realise successive losses, then he will be more prone to invest in risky assets. The
relationship between the mental accounting and the covariance is characterised by week intensity. This is
due to the cognitive illusion of the Tunisian investors. The majority of them ignore the role of covariance.
Our results highlight that the diversification level is a consequence of the mental accounting bias. This
relationship goes until a value of 1.7. It is clear that the “diversification” concept is closed to the
behavioural concepts. It may be considered as a “Concept of connection” between these two theories of
portfolio choice since it is a function of all the behavioural concepts in our cognitive model.
In the second area of communication, we find that influences aren’t very intense. Only the mean-variance
concept “diversification” intensely affects the safety aim [a47 = 2.1].
4.1. Concepts weights based analysis
We use weights to study the intensity of the influences exert by the mean-variance concepts on the
behavioral concepts. Inversely, we use weights to measure the effects of behavioral concepts on the
rational mean-variance concepts.
We find that the “Diversification” is the most active concept on the first area of communication with a
weight of (4.50). Discussions with investors from our sample let us deducting that this concept is very clear
in their minds. The covariance and variance seem having a week influences on behavioral concepts.
The “Mental accounting” bias and “Emotions” exert influences on the mean-variance concept respectively
with a weight of (4.50) and (4.00). We find also that the “Safety aim” is more active than the “Potential
aim”. Departing from this finding, we can predict that the Tunisian investors are “safety first investors” as
described by Roy (1952).
Table [5] summarizes the received influences’ weight of concepts. It is observable that the “Diversification”
and the “Safety aim” are the most receiver concepts. There weights and reflect that they are the
most influenced concepts. As it mentioned before, the Tunisian investors are aware about the role of the
“diversification” of their portfolio. They tend to avoid losses and the majority of them are attracted by a
“safety aim”.
We notice that investors’ emotions and mental accounting have a law weight and
. Our finding may be explained by the fact of their behavioral nature. There are generally
spontaneous mechanisms.
The total weight of concepts can be held as a criterion to detect their capacity on linking the two theories of
portfolio choice. Table [6] shows that the “Diversification” can be considered as the best variable of
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Vol 4, No.2, 2012
connection that can assure the linking action. The behavioural concept “Safety aim” and the “Mental
accounting” can reinforce this relationship. The “Variance “and the “Covariance”, two concepts with a
technical aspect have the lowest total weights.
Figure [1] represents the average cognitive map of investors. We only draw the cognitive maps that
correspond to the zones of communications in order to detect all the relationships between the
mean-variance concepts of portfolio choice and the behavioural concepts. The most remarkable thing is that
these concepts are combined together in the cognitive schema of investors. The results highlight the impact
of psychological factors on the portfolio choice’s decision. For example, the investors’ “Emotions” can
orient his choice in term of portfolio level of diversification. Our results confirm the theoretical predictions
of the Lopes’ (1987) two factors theory. Emotions affect the decision making process. In the case of
portfolio choice, Emotions stimulate the presence of a safety aim or a potential aim that affect the wealth’s
allocation.
It‘s clear that investors are not fully rational to act as prescribed by the mean-variance theory when
constructing their portfolios. Our finding highlights that the mean-variance concepts are present in their
spatial cognitive but they are frapped by their psychology and emotions. We can affirm that the two theories
of portfolio choice are cognitively interrelated. The existence of concepts from both theories argues that is a
complementarities’ relationship.
5. Empirical implications
Traditional managers of portfolio exploit information about the stock market while the behavioural
managers exploit investors’ behaviour (Russell J.F., 1998). This is because as we mentioned before, the
literature is silent about the existence and the nature of the relationships between these two theories of
portfolio choice. We find that, in the real word of portfolio choice, investors combine between the two
theories of portfolio choice. In their cognitive schema, concepts are linked and their choices on terms of
portfolio’s diversification, volatility’s level… are affected by the investors emotions, the presence of a
potential or safety aims and by his mental accounting.
It is time now to generate some models that both exploit the market information and the investors’
behaviour. Models that should be useful (practical) and that integrate investor’s psychology and emotions.
6. Conclusion
The rational mean-variance theory (Markowitz 1952, 1959) affirms that investors are rational enough, so
they can maximize their utility function. They use a practical tool “the mean-variance” optimizer.
However, with the emergence of behavioural finance, the domain of portfolio management should integrate
new dimensions such as investors’ psychology (Kahneman and Tversky, 1979) and emotions (Lopes, 1987).
In this study we demonstrate that these two theories are interrelated in the cognitive schema of investors
from our sample. We use a methodology based on cognitive mapping. The originality of our study derives
from the creation of two communications’ zones and the detection of some “concepts of connection”. Our
results show the existence of complementarities between the rational and the behavioural theories of
portfolio choice since the average cognitive map demonstrate the presence of both technical concepts and
other behavioural concepts. They use the mean-variance technique and it will be moderated by their
emotions and psychological state.
References
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Bougon, M., Weick, K., and D., Binkhorst, (1977), “Cognition in organization: an analysis of the Utrecht
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Psychology, 20, 255-295.
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Vol 4, No.2, 2012
Table1. The basic concepts from the rational and the behavioral portfolio theories
Theories Basic concepts
Mean-Variance Theory Variance, Covariance, Expected return and Diversification
Behavioral Portfolio Theory Emotions, Safety aim, Potential aim and Mental accounting
Table2. The form of the adjacency matrix j1 :Variance
j2 :Covariance
Return
j3
j4 :Diversification
j5 :Emotions
j6 :Potential aim
j7 :Safety aim
accounting
j8:Mental
:Expected
Ci / Cj
i1 :Variance a11 a12 a13 a14 a15 a16 a17 a18
i2 :Covariance a21 a22 a23 a24 a25 a26 a27 a28
i3 :Expected Return a31 a32 a33 a34 a35 a36 a37 a38
i4 :Diversification a41 a42 a43 a44 a45 a46 a47 a48
i5 :Emotions a51 a52 a53 a54 a55 a56 a57 a58
i6 :Potential aim a61 a62 a63 a64 a65 a66 a67 a68
i7 :Safety aim a71 a72 a73 a74 a75 a76 a77 a78
8 :Mental accounting a81 a82 a83 a84 a85 a86 a87 a88
Table 3. The adjacency matrix and the zones of interactions between the two theories of portfolio choice
Var. Cov. Exp. R Divers. Emot. Pot. Saf. Ment.
Var. 0 0,5 0,9 0,6 0,1 0 0,5 0.6
Cov 0,2 0 0,3 0,2 0 0,2 0,2 0,1
Exp. R 0,2 0,2 0 0 0,2 0.9 1,2 0
Divers. 0,4 0,1 0,3 0 0,9 0,8 2,1 0.7
Emot. 0,4 0,9 0,9 1,8 0 1,8 2,5 0
Pot. 0,5 0,7 0,5 0,7 1,7 0 0,6 0
Saf. 0,7 0,7 0,4 1,7 2,1 1,3 0 0,7
Ment. 1,4 0.2 1,2 1,7 1,5 1,7 1,5 0
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Vol 4, No.2, 2012
Figure 1: The average cognitive map of Tunisian investors
The red color represents influences exert by mean-variance concepts to behavioral concepts.
The black color represents influences exert by behavioral concepts to mean-variance concepts
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