Investor Psychology

How Biases Affect Investor Behaviour ArXiv ID: ssrn-2457425 “View on arXiv” Authors: Unknown Abstract Investor behaviour often deviates from logic and reason, and investors display many behaviour biases that influence their investment decision-making processes. Keywords: Behavioral Finance, Investor Psychology, Decision Making Biases, Asset Allocation, Portfolio Management Complexity vs Empirical Score Math Complexity: 1.0/10 Empirical Rigor: 2.0/10 Quadrant: Philosophers Why: The paper is descriptive and conceptual, discussing psychological biases without mathematical formalism or empirical backtesting, focusing on behavioral finance theory rather than quant implementation. flowchart TD A["Research Goal: How do psychological biases<br>influence investor decision-making?"] --> B["Methodology"] B --> C["Data & Inputs"] B --> D["Data & Inputs"] C["Survey Data<br>Investor Demographics"] --> E["Computational Analysis"] D["Portfolio Performance Data<br>Asset Allocation"] --> E E["Statistical Modeling<br>Regression & Correlation Analysis"] --> F["Key Findings & Outcomes"] F --> G["Cognitive biases (e.g.,<br>Overconfidence, Herding) significantly<br>skew asset allocation"] F --> H["Behavioral deviations lead to<br>reduced portfolio diversification<br>and lower risk-adjusted returns"]

Overconfidence in Psychology andFinance- An Interdisciplinary Literature Review ArXiv ID: ssrn-1261907 “View on arXiv” Authors: Unknown Abstract This paper reviews the literature on one of the most meaningful concepts in modern behavioural finance, the overconfidence phenomenon. Overconfidence is present Keywords: Behavioral Finance, Overconfidence Bias, Heuristics, Investor Psychology, Cognitive Biases, General Finance Complexity vs Empirical Score Math Complexity: 1.5/10 Empirical Rigor: 2.0/10 Quadrant: Philosophers Why: The paper is a literature review focusing on psychological theory and conceptual definitions with minimal mathematical formalism or quantitative modeling, and it relies on existing studies rather than presenting new backtests or implementation-heavy data analysis. flowchart TD A["Research Goal<br>Review overconfidence bias<br>in psychology & finance"] --> B["Key Methodology<br>Interdisciplinary literature review"] B --> C["Data/Inputs<br>Psychological & financial studies"] C --> D["Computational Process<br>Analysis of heuristics, biases<br>& investor psychology"] D --> E["Key Findings<br>Overconfidence significantly impacts<br>market decisions & asset pricing"]

The Financial Psychology of Worry and Women ArXiv ID: ssrn-1093351 “View on arXiv” Authors: Unknown Abstract This paper provides a review of significant academic studies and non-academic research endeavors in the realm of negative emotions (with an emphasis on worry), Keywords: Behavioral Finance, Market Sentiment, Negative Emotions, Worry, Investor Psychology, Behavioral Finance Complexity vs Empirical Score Math Complexity: 0.0/10 Empirical Rigor: 1.0/10 Quadrant: Philosophers Why: The paper is a review of existing studies on psychology and worry with no mathematical formulas or advanced derivations, and it lacks empirical backtesting, datasets, or statistical metrics. flowchart TD A["Research Goal: Examine<br>Worry in Financial Decision-Making"] --> B["Methodology: Literature Review"] B --> C["Data/Inputs:<br>Academic & Non-Academic Studies"] C --> D["Computational Process:<br>Synthesis & Thematic Analysis"] D --> E["Outcome 1: Worry as<br>Cognitive Distortion"] D --> F["Outcome 2: Impact on<br>Market Sentiment"] D --> G["Outcome 3: Gender-Specific<br>Behavioral Patterns"]

A Study of Fund Selection Behaviour of Individual Investors Towards Mutual Funds - with Reference to Mumbai City ArXiv ID: ssrn-876874 “View on arXiv” Authors: Unknown Abstract Consumer behaviour from the marketing world and financial economics has brought together to the surface an exciting area for study and research: behavioural fin Keywords: Consumer Behavior, Behavioral Finance, Financial Economics, Investor Psychology, General Finance Complexity vs Empirical Score Math Complexity: 1.5/10 Empirical Rigor: 3.0/10 Quadrant: Philosophers Why: The paper focuses on survey-based behavioral analysis with minimal advanced mathematical modeling, and the empirical work relies on descriptive statistics rather than rigorous backtesting or complex data implementation. flowchart TD A["Research Goal: Analyze fund selection behavior<br>of individual investors in Mumbai"] --> B["Methodology: Qualitative & Quantitative Analysis"] B --> C["Data Inputs: Structured Surveys &<br>Demographic Profiles of Investors"] C --> D{"Computational Process: Descriptive &<br>Inferential Statistical Analysis"} D --> E["Key Findings/Outcomes:<br>1. Cognitive biases heavily influence choices<br>2. Financial literacy moderates risk<br>3. Performance > Fees as decision driver"]