Can prospect theory explain the disposition effect? An analysis based on value function

2018 ◽  
Vol 8 (3) ◽  
pp. 235-255
Author(s):  
Xiaotian Liu ◽  
Huayue Zhang ◽  
Shengmin Zhao
Keyword(s):  
Prospect Theory ◽  
Portfolio Choice ◽  
Crucial Role ◽  
Value Function ◽  
Disposition Effect ◽  
Dynamic Programming Method ◽  
Prediction Ability ◽  
Content Type ◽  
The Impact ◽  
The Value Function

Purpose The prospect theory is potentially an essential ingredient in modeling the disposition effect. However, many scholars have tried to explain the disposition effect with the help of prospect theory and they came to opposite conclusions. The purpose of this paper is to examine the impact of value function of the prospect theory on predicting the disposition effect. Design/methodology/approach Lagrange multiplier optimization and dynamic programming method are used to solve the representative investor’s optimal portfolio choice problem. Furthermore, numerical simulation is used to compare the prediction ability of different types of value function. Findings The authors support that the value function has a crucial role in predicting the disposition effect with prospect theory, i.e. the curvature and boundedness of the value function may influence the performance of applying the prospect theory in the disposition effect. They conclude that a piecewise negative exponential value function can predict the disposition effect, while others like the piecewise power value function may not. Originality/value Extant literature about modeling the disposition effect with the prospect theory mostly focus on the time when gain-loss utility occurs or the selection of reference point. This paper based on the value function properties provides a new perspective in analyzing the crucial role that value function has in predicting financial market anomalies.

scholarly journals A Simulation Approach to Statistical Estimation of Multiperiod Optimal Portfolios

2012 ◽  
Vol 2012 ◽  
pp. 1-13
Author(s):  
Hiroshi Shiraishi
Keyword(s):  
Portfolio Choice ◽  
Value Function ◽  
Sample Path ◽  
Optimal Investment ◽  
Investment Strategy ◽  
Time Dependency ◽  
Portfolio Rebalancing ◽  
Sample Paths ◽  
Optimal Investment Strategy ◽  
The Value Function

This paper discusses a simulation-based method for solving discrete-time multiperiod portfolio choice problems under AR(1) process. The method is applicable even if the distributions of return processes are unknown. We first generate simulation sample paths of the random returns by using AR bootstrap. Then, for each sample path and each investment time, we obtain an optimal portfolio estimator, which optimizes a constant relative risk aversion (CRRA) utility function. When an investor considers an optimal investment strategy with portfolio rebalancing, it is convenient to introduce a value function. The most important difference between single-period portfolio choice problems and multiperiod ones is that the value function is time dependent. Our method takes care of the time dependency by using bootstrapped sample paths. Numerical studies are provided to examine the validity of our method. The result shows the necessity to take care of the time dependency of the value function.

Digital transformation: “jobocolypse” or empowerment?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zeynep Hizir
Keyword(s):  
Human Resources ◽  
Crucial Role ◽  
Design Methodology ◽  
Industrial Revolution ◽  
Digital Transformation ◽  
Evidence Based ◽  
Content Type ◽  
Fourth Industrial Revolution ◽  
Industry Research ◽  
The Impact

Purpose The purpose of this paper is to analyse the impact of digital transformation on jobs and to assess whether or not the so-called Fourth Industrial Revolution will lead to mass redundancies. The piece also looks at the role human resources (HR) departments will have to play in the implementation of, and response to, digital transformation within the workplace. Design/methodology/approach This paper combines research based on media articles, a parliamentary report and wider digital transformation industry research. The author looks to explain what digital transformation is, deconstruct misconceptions around digital transformation, assess the true evidence-based impact of digital transformation on jobs and advise HR departments on the impact of digital transformation within the workplace. Findings This piece finds that there remains a considerable degree of misunderstanding and many misconceptions around digital transformation and that while digital transformation will lead to the loss of some jobs, it will also lead to the change of existing ones and creation of new ones. Furthermore, this piece finds that HR departments will play a crucial role in the implementation of digital transformation, but that they too will need to pivot and adjust to new workplace realities as a result. Originality/value Many HR departments face confusion and misconceptions around the impact of digital transformation on the workforce, and there also remains concern among many employers that technology will replace their jobs. This piece seeks to dispel the myths and paint a clearer picture to both HR departments and employees around the impact of digital transformation.

A study of prominence for disposition effect: a systematic review

2019 ◽  
Vol 11 (1) ◽  
pp. 2-21 ◽  
Author(s):  
Syed Aliya Zahera ◽  
Rohit Bansal
Keyword(s):  
Mutual Funds ◽  
Behavioral Finance ◽  
Mutual Fund ◽  
Institutional Investors ◽  
Disposition Effect ◽  
Individual Investors ◽  
Content Type ◽  
Experimental Market ◽  
The Individual ◽  
The Impact

Purpose The purpose of this paper is to study the disposition effect that is exhibited by the investors through the review of research articles in the area of behavioral finance. When the investors are hesitant to realize the losses and quick to realize the gains, this phenomenon is known as the disposition effect. This paper explains various theories, which have been evolved over the years that has explained the phenomenon of disposition effect. It includes the behavior of individual investors, institutional investors and mutual fund managers. Design/methodology/approach The authors have used the existing literatures from the various authors, who have studied the disposition effect in either real market or the experimental market. This paper includes literature over a period of 40 years, that is, Dyl, 1977, in the form of tax loss selling, to the most recent paper, Surya et al. (2017). Some authors have used the PGR-PLR ratio for calculating the disposition effect in their study. However, some authors have used t-test, ANNOVA, Correlation coefficient, Standard deviation, Regression, etc., as a tool to find the presence of disposition effect. Findings The effect of disposition can be changed for different types of individual investors, institutional investors and mutual funds. The individual investors are largely prone to the disposition effect and the demographic variables like age, gender, experience, investor sophistication also impact the occurrence of the disposition effect. On the other side, the institutional investors and mutual funds managers may or may not be affected by the disposition effect. Practical implications The skilled understanding of the disposition effect will help the investors, financial institutions and policy-makers to reduce the adverse effect of this bias in the stock market. This paper contributes a detailed explanation of disposition effect and its impacts on the investors. The study of disposition effect has been found to be insufficient in the context of Indian capital market. Social implications The investors and society at large can gains insights about causes and influences of disposition effect which will be helpful to create sound investment decisions. Originality/value This paper has complied the 11 causes for the occurrence of disposition effect that are found by the different authors. The paper also highlights the impact of the disposition effect in the decision-making of various investors.

The impact of Mad Money recommendations during bull and bear markets

2016 ◽  
Vol 12 (1) ◽  
pp. 52-70 ◽  
Author(s):  
Adam J. Roszkowski ◽  
Nivine Richie
Keyword(s):  
Prospect Theory ◽  
Behavioral Finance ◽  
Abnormal Returns ◽  
Good News ◽  
Content Type ◽  
Bear Market ◽  
Bear Markets ◽  
The Impact ◽  
Investor Reaction ◽  
Bull And Bear Markets

Purpose – The purpose of this paper is to examine semi-strong market efficiency by observing the behavioral finance implications of Jim Cramer’s recommendations in bull vs bear markets. The authors extend the literature by analyzing investor reaction through the lenses of prospect theory, overreaction, and herding. Design/methodology/approach – The authors test for abnormal returns in response to Mad Money buy and sell recommendations. The authors use a sample of buy and sell recommendations from MadMoneyRecap.com from July 28, 2005 through February 9, 2009. The 3.5-year time period is the most recent and comprehensive set of Mad Money recommendations that has been tested to date. Findings – The results indicate market inefficiency at the semi-strong level. Furthermore, the findings highlight the loss aversion tendencies of investors in regards to prospect theory of Kahneman and Tversky (1979) as well as the disposition effect of Shefrin and Statman (1985). Evidence also exists consistent with the herding and overreaction hypotheses. Practical implications – The evidence suggests contrarian behavior in which investors respond positively to good news in bad times – perhaps, in effort to stay the course and at least break even. This behavior may suggest that losers tend to hold on to losses in hopes of recouping them. Thus, positive information in bad times could further persuade market participants to hang on to or buy more of losers, while also persuading non-shareholders to buy in as well. Originality/value – Though other studies including Kenny and Johnson (2010) have estimated abnormal returns in response to analyst recommendations, to the knowledge, none has examined behavioral implications of investor reaction to buy and sell recommendations in both bull and bear markets. Furthermore, the study captures a longer bull and bear market and covers two definitions of such markets.

scholarly journals A DECISION-MAKING FRAMEWORK BASED ON THE PROSPECT THEORY UNDER AN INTUITIONISTIC FUZZY ENVIRONMENT

2018 ◽  
Vol 24 (6) ◽  
pp. 2374-2396 ◽  
Author(s):  
Jing Gu ◽  
Zijian Wang ◽  
Zeshui Xu ◽  
Xuezheng Chen
Keyword(s):  
Decision Making ◽  
Prospect Theory ◽  
Value Function ◽  
Behavior Pattern ◽  
Weighting Function ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Decision Making Framework ◽  
Decision Making Behavior ◽  
The Value Function

Uncertainty and ambiguity are frequently involved in the decision-making process in our daily life. This paper develops a generalized decision-making framework based on the prospect theory under an intuitionistic fuzzy environment, by closely integrating the prospect theory and the intuitionistic fuzzy sets into our framework. We demonstrate how to compute the intuitionistic fuzzy prospect values as the reference values for decision-making and elaborate a four-step editing phase and a valuation phase with two key functions: the value function and the weighting function. We then conduct experiments to test our decision- making methodology and the key features of our framework. The experimental results show that the shapes of the value function and the weighting function in our framework are in line with those of prospect theory. The methodology proposed in this paper to elicit prospects that are not only under uncertainty but also under ambiguity. We reveal the decision-making behavior pattern through comparing the parameters. People are less risk averse when making decisions under an intuitionistic fuzzy environment than under uncertainty. People still underestimate the probability of the events in our experiment. Further, the choices of participants in the experiments are consistent with the addition and multiplication principles of our framework.

Dynamic multi-attribute decision-making method with three-parameter interval grey number based on the prospect theory

2018 ◽  
Vol 8 (4) ◽  
pp. 424-435 ◽  
Author(s):  
Ye Li ◽  
Dongxing Zhang
Keyword(s):  
Decision Making ◽  
Prospect Theory ◽  
Value Function ◽  
Reference Points ◽  
Content Type ◽  
Time Points ◽  
Decision Method ◽  
Multi Attribute Decision Making ◽  
Parameter Interval ◽  
Grey Number

Purpose The purpose of this paper is to propose a dynamic multi-attribute decision-making method based on the prospect theory for dealing with the dynamic multi-attribute decision-making problem with three-parameter interval grey number. Design/methodology/approach First, the kernel and comparison rule of three-parameter interval grey numbers are defined, which are the basis of collecting and sorting grey numbers. Next, the prospect value function is determined in view of the decision-making information with different time points as the reference points. Then, an optimal model for solving the attribute weight and time weight is constructed based on the grey entropy principle. Findings The paper provides a dynamic grey interrelation decision method based on the prospect theory with three-parameter interval grey number, and the example analysis shows that the method proposed in this paper has validity and rationality. Research limitations/implications If we have a better understanding of the weights of different reference points, it is possible to receive a more reasonable expression for the comprehensive prospect utility value function. Practical implications The paper provides a grey interrelation decision method based on the prospect theory, which can help the decision maker deal with the dynamic multi-attribute decision-making problems under the uncertain environment. Originality/value The paper proposes the kernel and ranking method of three-parameter interval grey number, and uses different time points as the reference points to define the prospect value function. Furthermore, this paper structures a dynamic grey interrelation decision method with three-parameter interval grey number based on the prospect theory.

The Relationship Between Numeracy and the Value Function and Probability Weighting in Prospect Theory

2012 ◽  
Author(s):  
Mona Gauth ◽  
Maria Henriksson ◽  
Peter Juslin ◽  
Neda Kerimi ◽  
Marcus Lindskog ◽  
...  
Keyword(s):  
Prospect Theory ◽  
Value Function ◽  
Probability Weighting ◽  
The Relationship ◽  
The Value Function

Antecedents to heuristics: decoding the role of herding and prospect theory for Indian millennial investors

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Preeti Goyal ◽  
Poornima Gupta ◽  
Vanita Yadav
Keyword(s):  
Prospect Theory ◽  
Mutual Funds ◽  
Mutual Fund ◽  
Future Research ◽  
Content Type ◽  
Financial Investment ◽  
Financial Products ◽  
Financial Planners ◽  
The Impact

PurposeThe purpose of this paper is to explore how heuristics are formed and whether herding and prospect theory act as antecedents to heuristics. The relationship is explored specifically for millennials.Design/methodology/approachThe proposed relationship is explored specifically for millennials. Herding and prospect theory are modelled as antecedents to heuristics. The study uses survey data from 923 millennials from India to test the model for two financial products: equity and mutual funds. Regression analysis is used to evaluate the model.FindingsFindings support the role of herding and prospect theory as antecedents to heuristics of millennials although to varying degrees for equity and mutual fund investments. The impact of herding on heuristics is likely to be smaller for equity investments as compared to mutual fund investments.Research limitations/implicationsThe findings provide insights into how heuristics are formed for millennials. The findings add to literature by beginning a new line of inquiry on how heuristics are formed. Since the model is tested on a single generation, future research can test the model on other generations. In addition, future research can also add more antecedents to our proposed model.Practical implicationsFindings from this study can provide financial planners and marketers with an understanding of how heuristics are formed for millennials. Financial planners can use these insights while providing financial advice to this generation and marketers can use them to create more relevant outreach.Social implicationsFinancial investments are an important conduit for financial security. By understanding the cognitive processes that influence financial investment decision-making, it is possible for educators to create content appropriately and for financial planners to advise clients accordingly to enable optimal financial decisions that will be wealth-creating.Originality/valueExisting literature primarily treats heuristics, herding and prospect theory as being independent of each other. The authors take a novel approach to model the antecedents to heuristics to be herding and prospect theory. The model is tested on millennials for two financial products: equity and mutual funds.

Individual investor attention to stock split and the disposition effect

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wendy Kesuma ◽  
Irwan Adi Ekaputra ◽  
Dony Abdul Chalid
Keyword(s):  
Stock Returns ◽  
Private Information ◽  
Stock Exchange ◽  
Stock Splits ◽  
Disposition Effect ◽  
Individual Investors ◽  
Investor Attention ◽  
Content Type ◽  
Stock Split ◽  
The Impact

PurposeThis paper investigates whether individual investors are attentive to stock splits and whether higher split ratios (stronger private information signals) reduce the disposition effect.Design/methodology/approachThis study employs stock split events and transaction data in the Indonesia Stock Exchange (IDX) from January 2004 to December 2017. The authors measure individual investors' attention using buy-initiated trades. To test the effect of split signal on disposition effect, the authors regress individual investors' sell-initiated trades on past stock returns.FindingsUnlike Birru (2015), the authors find that individual investors are attentive to stock splits, especially when stock split ratios are high. In turn, stock splits tend to weaken the disposition effect. The higher the stock split ratios, the weaker the disposition effect.Research limitations/implicationsThis study has a limitation in that the authors exclude all stock splits with dividend events around the split date. These stock splits cover 37% of all splits in Indonesia.Practical implicationsPractically, individual investors should look for stock-related information to reduce disposition bias.Originality/valueTo the best of authors’ knowledge, this study is the first to test individual investors' attention on stock splits based on their buy-initiated trades. This study is also the first to test the impact of stock split ratios on the disposition effect reduction. This study's findings enrich the scant literature on individual investors' attention and how to reduce their disposition effect bias.

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