Behavioral Finance and Decision Theory in Investment Management: An Overview

1995 ◽  
Vol 1995 (7) ◽  
pp. 1-1 ◽  
Author(s):  
Arnold S. Wood
Keyword(s):  
Decision Theory ◽  
Behavioral Finance ◽  
Investment Management

Behavioral Decision Theory

2020 ◽  
Author(s):  
Kazuhisa Takemura
Keyword(s):  
Decision Making ◽  
Decision Theory ◽  
Behavioral Economics ◽  
Behavioral Finance ◽  
Utility Theory ◽  
Normative Theory ◽  
Behavioral Decision Theory ◽  
Behavioral Decision ◽  
Descriptive Theory ◽  
Human Decision

Behavioral decision theory is a descriptive psychological theory of human judgment, decision making, and behavior that can be applied to political science. Behavioral decision theory is closely related to behavioral economics and behavioral finance. Behavioral economics is an attempt to understand actual human economic behavior, and behavioral finance studies human behavior in financial markets. Research on people’s decision making represents an important part of these fields, in which various aspects overlap with the scope of behavioral decision theory. Behavioral decision theory focuses on the decision-making phenomena that are broadly divisible into those under certainty, those under risk, and others under uncertainty that includes ambiguity and ignorance. What are the theoretical frameworks that could be used to explain the decision-making phenomenon? Although numerous theories related to decision making have been developed, they are, in essence, often broadly divided into two types: normative theory and descriptive theory. The former is intended to support rational decision making. The latter describes how people actually make decisions. Both normative and descriptive theories reflect the nature of actual human decision making to a degree. Even descriptive theory seeks a certain level of rationality in actual human decision making. Consequently, the two are mutually indistinguishable. Nonetheless, a major example of normative theory is regarded as the system of utility theory that is widely used in economics. A salient example of descriptive theory is behavioral decision theory. Utility theory has numerous variations, such as linear and nonlinear utility theories. Most theories have established axioms and mathematically developed principles. In contrast, behavioral decision theory covers a considerably wide range of variations of theoretical expressions, including theories that have been developed mathematically (such as prospect theory) and those expressed only with natural language (such as multiattribute decision-making process models). Behavioral decision theory has integrated the implications of the normative theory, descriptive theory, and prescriptive theory that help people to make better decisions.

Behavior of fund managers in Malaysian investment management industry

2017 ◽  
Vol 9 (3) ◽  
pp. 205-239 ◽  
Author(s):  
Zamri Ahmad ◽  
Haslindar Ibrahim ◽  
Jasman Tuyon
Keyword(s):  
Bounded Rationality ◽  
Behavioral Finance ◽  
Asset Management ◽  
Institutional Investors ◽  
Institutional Investor ◽  
Current Paper ◽  
Investor Behavior ◽  
Investment Management ◽  
Content Type ◽  
Fund Managers

PurposeThis paper aims to explore the relevance of bounded rationality to the practice of institutional investors in Malaysia. Understanding institutional investor behavior is important, as it can determine the asset prices and consequently the market behavior. Design/methodology/approachA set of questionnaires is used to solicit information regarding the understanding and practical application of behavioral finance theories and strategies among fund managers in the Malaysian investment management practice. In the process, bounded rational theory is aimed to be validated. Fund managers’ possible bounded rational behavior is assessed with reference to their investment management approaches and strategies right from individual beliefs and acquisition of information, as well as investment management and strategies used. FindingsThe findings lend support to the notion that institutional investors too, being normal human beings, are expected to think and behave in a boundedly rational manner as postulated in bounded rational theory. The sources of bounded rationality are individual, institutional and social forces. Thus, portfolio trading and investment management strategies are exposed to wide varieties of behavioral risks. Despite the notions that behavioral risks are real and the impact on fund performance could be pervasive, fund managers’ self-awareness regarding control and institutional readiness to govern behavioral risks in investment practices is still low. Research limitations/implicationsEmpirical evidence drawn in the current paper is subjected to small sample size and specific focus on Malaysian context. Despite this limitation, the sample is statistically sufficient and provides a fair representation, as well as quality opinions, of fund manager’s investment management behavior in Malaysia. This research provides valuable implications to practitioners (fund managers) and regulators (investment management and capital market policymakers). In practice, the current study draws some practical ideas, especially for buy-side institutional investors, on the source and impact of behavioral biases on fund management practices and performance. For regulators, this research highlighted the needs and possible ways to regulate these behavioral risks. Originality/valueThe current paper provides new insights on the theory and practice of the institutional investor. In theory, this research provides evidence of bounded rationality of institutional investor behavior, practicing in the asset management industry in the emerging markets of Malaysia. This evidence lends support to the validity of the bounded rationality theory in explaining institutional investor behavior. In practice, thisresearch provides new insights on the relevance of behavioral finance perspectives and strategies in the asset management industry practice and policy.

Representation, abstraction, and simple-minded sophisticates

2020 ◽  
Vol 43 ◽  
Author(s):  
Peter Dayan
Keyword(s):  
Decision Theory ◽  
Predictive Coding ◽  
Bayesian Decision Theory ◽  
Bayesian Decision ◽  
Model Based ◽  
Model Free

Abstract Bayesian decision theory provides a simple formal elucidation of some of the ways that representation and representational abstraction are involved with, and exploit, both prediction and its rather distant cousin, predictive coding. Both model-free and model-based methods are involved.

Giving advice: Decision theory perspectives on sexual assault.

1992 ◽  
Vol 47 (4) ◽  
pp. 577-588 ◽  
Author(s):  
Baruch Fischhoff
Keyword(s):  
Sexual Assault ◽  
Decision Theory

Rational Uses of Decision Theory

PsycCRITIQUES ◽  
2009 ◽  
Vol 54 (42) ◽  
Author(s):  
Gordon Pitz
Keyword(s):  
Decision Theory

The Measurement of Performance in Probabilistic Diagnosis IV. Utility Considerations in Therapeutics and Prognostics

1981 ◽  
Vol 20 (02) ◽  
pp. 80-96 ◽  
Author(s):  
J. D. F. Habbema ◽  
J. Hilden
Keyword(s):  
Decision Theory ◽  
Figure Of Merit ◽  
Acute Abdominal Pain ◽  
Theory Approach ◽  
Expected Loss ◽  
Patient Benefit ◽  
Evaluation Approach ◽  
Average Loss ◽  
Actual Decision ◽  
Probabilistic Diagnosis

It is argued that it is preferable to evaluate probabilistic diagnosis systems in terms of utility (patient benefit) or loss (negative benefit). We have adopted the provisional strategy of scoring performance as if the system were the actual decision-maker (not just an aid to him) and argue that a rational figure of merit is given by the average loss which patients would incur by having the system decide on treatment, the treatment being selected according to the minimum expected loss principle of decision theory.A similar approach is taken to the problem of evaluating probabilistic prognoses, but the fundamental differences between treatment selection skill and prognostic skill and their implications for the assessment of such skills are stressed. The necessary elements of decision theory are explained by means of simple examples mainly taken from the acute abdomen, and the proposed evaluation tools are applied to Acute Abdominal Pain data analysed in our previous papers by other (not decision-theoretic) means. The main difficulty of the decision theory approach, viz. that of obtaining good medical utility values upon which the analysis can be based, receives due attention, and the evaluation approach is extended to cover more realistic situations in which utility or loss values vary from patient to patient.

The Process of Medical Diagnosis: Routes of Mathematical Investigations

1978 ◽  
Vol 17 (01) ◽  
pp. 1-10 ◽  
Author(s):  
P. Tautu ◽  
G. Wagner
Keyword(s):  
Decision Theory ◽  
Medical Diagnosis ◽  
Pattern Analysis ◽  
Logical Probability ◽  
Inquiry Process ◽  
Fuzzy Subsets

This paper is an analysis of the most important mathematical aspects of medical diagnosis: logical probability, rationality and decision theory, gambling models, pattern analysis, hazy and fuzzy subsets theory and, finally, the stochastic inquiry process.

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