Behavioural Biases and Investment Decision Making – Key Vocabulary

Vocabulary flashcards covering core concepts, biases, statistical terms, and methodological elements from the lecture notes on behavioural biases and investment decision making.

Behavioral Finance

A field that blends psychology and sociology with traditional finance to explain how cognitive biases affect financial markets and investor decisions.

Behavioral Bias

A systematic deviation from rational judgment that consistently influences investors’ decisions.

Loss Aversion

Bias where the pain of losses outweighs the pleasure of equivalent gains, prompting investors to hold losing assets or avoid selling at a loss.

Representativeness Bias

A heuristic in which investors judge probabilities by comparing current situations to past patterns, often ignoring true statistical likelihoods.

Overconfidence Bias

An inflated belief in one’s own investment skill or knowledge, leading to underestimated risk and excessive trading.

Prospect Theory

Daniel Kahneman and Amos Tversky’s theory describing how people choose between risky alternatives, emphasizing loss aversion and reference dependence.

Heuristic Theory

Kahneman & Tversky’s concept that people use mental shortcuts (heuristics) like representativeness, anchoring, and availability when making complex decisions.

Efficient Market Hypothesis (EMH)

Eugene Fama’s theory that asset prices fully reflect all available information, making it impossible to consistently outperform the market.

Mental Accounting

Richard Thaler’s idea that individuals separate finances into mental buckets, increasing sensitivity to gains or losses within each bucket.

Disposition Effect

Tendency to sell winning stocks too early and hold losing stocks too long due to loss aversion.

Herding Effect

Bias where investors imitate the trades of a larger crowd rather than relying on their own information.

Illusion of Control

The belief, studied by Langer, that individuals can influence outcomes in inherently uncertain situations, fueling overconfidence.

Speculative Bubble

A market phenomenon where asset prices exceed intrinsic values, often driven by overconfidence and herd behavior.

Investment Decision Making

The process of allocating capital among various assets—in this study, individual choices within the stock market.

Dependent Variable (DV)

The outcome a study seeks to explain; here, investment decision making.

Independent Variable (IV)

A factor believed to influence the DV; in this research: loss aversion, representativeness, and overconfidence.

Conceptual Framework

A visual or written model outlining relationships between study variables and guiding hypothesis development.

Hypothesis

A testable statement predicting how an independent variable affects a dependent variable.

Primary Data

Information collected firsthand by researchers—e.g., survey responses from Nepalese investors.

Convenience Sampling

Non-probability method where respondents are selected based on accessibility and willingness to participate.

Likert Scale

A psychometric scale (e.g., 1–5 from Strongly Disagree to Strongly Agree) used to measure attitudes in questionnaires.

Cronbach’s Alpha

Statistic measuring internal consistency of survey items; values closer to 1 indicate higher reliability.

Descriptive Statistics

Techniques (mean, standard deviation) that summarize and describe dataset characteristics.

Inferential Statistics

Methods (correlation, regression, ANOVA) that draw conclusions about a population based on sample data.

Pearson Correlation Coefficient (r)

Metric ranging from –1 to +1 indicating strength and direction of a linear relationship between two variables.

Coefficient of Determination (R²)

Proportion of variance in the dependent variable explained by independent variables in a regression model.

Adjusted R-Squared

R² adjusted for the number of predictors, providing a more accurate model fit measure.

Regression Analysis

Statistical technique modeling how one or more independent variables predict a dependent variable.

ANOVA (Analysis of Variance)

Statistical test that determines whether regression model results are significant overall by comparing explained vs. unexplained variance.

Standard Error of the Estimate

Average distance between observed and predicted values in a regression, reflecting prediction accuracy.

p-Value

Probability of obtaining observed results if the null hypothesis is true; lower values (<0.05 or <0.01) suggest significance.

Null Hypothesis

Default assumption that an independent variable has no effect on the dependent variable; rejected when p-value is sufficiently low.

Overarching Finding

Key conclusion that overconfidence significantly affects investment decisions, while loss aversion and representativeness show positive but insignificant effects.

Action Implication

Practical recommendation derived from research findings, such as advising clients about bias or crafting regulatory policies.

Financial Literacy

Knowledge enabling individuals to understand financial products and biases, thereby improving decision quality.