Cognitive Biases

Behavioral Finance ArXiv ID: ssrn-2702331 “View on arXiv” Authors: Unknown Abstract Behavioral finance studies the application of psychology to finance, with a focus on individual-level cognitive biases. I describe here the sources of judgment Keywords: behavioral finance, cognitive biases, psychology, Equities Complexity vs Empirical Score Math Complexity: 3.0/10 Empirical Rigor: 2.0/10 Quadrant: Philosophers Why: The paper discusses behavioral biases and psychological concepts without employing advanced mathematical formulations or heavy empirical backtesting frameworks. It is more descriptive and theoretical, aligning with a philosophical approach to finance. flowchart TD A["Research Goal: Explore psychology in finance & cognitive biases"] --> B["Method: Literature Review & Analysis"] B --> C["Data: Academic Papers & Investor Studies"] C --> D{"Analysis of Biases"} D --> E["Identify Cognitive Mechanisms"] E --> F["Key Outcomes:<br/>Impact on Equities<br/>Market Inefficiencies"]

BehavioralFinance ArXiv ID: ssrn-2480892 “View on arXiv” Authors: Unknown Abstract Behavioral finance studies the application of psychology to finance, with a focus on individual-level cognitive biases. I describe here the sources of judgment Keywords: behavioral finance, cognitive biases, psychology, Equities Complexity vs Empirical Score Math Complexity: 2.0/10 Empirical Rigor: 1.0/10 Quadrant: Philosophers Why: The paper is a conceptual review focusing on psychological biases and theories, with minimal advanced mathematical formulas or empirical backtesting. It primarily discusses theoretical mechanisms and qualitative evidence. flowchart TD A["Research Goal: Investigate impact of cognitive biases on equities investment decisions"] --> B{"Methodology"}; B --> C["Data: Investor trading records & survey responses"]; B --> D["Experiment: Lab-based investment simulations"]; C --> E["Computational Process: Statistical analysis of bias indicators"]; D --> E; E --> F["Key Findings: Systematic biases lead to suboptimal portfolio performance"]; E --> G["Outcomes: Framework for predicting market anomalies"];

BehavioralFinance: An Introduction ArXiv ID: ssrn-1488110 “View on arXiv” Authors: Unknown Abstract This survey introduces and reviews the field of behavioral finance. It outlines the traditional finance approach, which builds upon rational acting investors, i Keywords: Behavioral Finance, Rational Investors, Cognitive Biases, Market Efficiency, General Finance Complexity vs Empirical Score Math Complexity: 1.5/10 Empirical Rigor: 2.0/10 Quadrant: Philosophers Why: This paper is a high-level survey that discusses theoretical concepts and empirical anomalies without presenting new mathematical models or implementation details for backtesting. flowchart TD A["Research Goal:<br/>Review Behavioral Finance Foundations"] --> B["Methodology:<br/>Literature Survey & Framework Analysis"] B --> C["Data/Inputs:<br/>Traditional Finance Models<br/>Cognitive Bias Studies"] C --> D{"Computational Process:<br/>Rational vs. Behavioral Comparison"} D --> E["Key Finding 1:<br/>Investors often deviate from rationality"] D --> F["Key Finding 2:<br/>Cognitive biases impact markets"] D --> G["Key Finding 3:<br/>Market efficiency challenged"] E & F & G --> H["Outcome:<br/>Integrated Behavioral Finance Framework"]

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"]

Behavioral Economics ArXiv ID: ssrn-245828 “View on arXiv” Authors: Unknown Abstract Behavioral Economics is the combination of psychology and economics that investigates what happens in markets in which some of the agents display human limitati Keywords: Behavioral Economics, Prospect Theory, Cognitive Biases, Heuristics, General (Economics) Complexity vs Empirical Score Math Complexity: 3.0/10 Empirical Rigor: 2.0/10 Quadrant: Philosophers Why: The paper is a theoretical and conceptual survey of behavioral economics, focusing on high-level ideas like bounded rationality and limits of arbitrage with minimal mathematical formalism or empirical data. It lacks backtests, datasets, or implementation details, positioning it as a philosophical/theoretical discussion rather than a quantitative trading strategy. flowchart TD A["Research Goal:<br>Understand deviations from<br>rational economic models"] --> B{"Methodology"} B --> C["Theoretical Modeling<br>e.g., Prospect Theory"] B --> D["Experimental Design<br>Labs & Field Studies"] C --> E["Data Inputs:<br>Psychological Heuristics &<br>Bias Observations"] D --> E E --> F["Computational Processes:<br>Agent-Based Simulation<br>& Probability Weighting"] F --> G{"Key Findings/Outcomes"} G --> H["Prospect Theory<br>Loss Aversion & Reference Dependence"] G --> I["Identified Cognitive Biases<br>e.g., Anchoring, Framing"] G --> J["Policy Implications<br>Nudges & Market Regulation"]

Behavioral Economics ArXiv ID: ssrn-245733 “View on arXiv” Authors: Unknown Abstract Behavioral Economics is the combination of psychology and economics that investigates what happens in markets in which some of the agents display human limitati Keywords: Behavioral Economics, Prospect Theory, Cognitive Biases, Heuristics, General (Economics) Complexity vs Empirical Score Math Complexity: 4.0/10 Empirical Rigor: 6.0/10 Quadrant: Street Traders Why: The paper involves established financial models and deterministic thresholds but lacks statistical backtesting or empirical datasets. The focus is on practical application and optimization within existing frameworks, fitting the Street Trader profile. flowchart TD A["Research Goal: Investigate market outcomes under human limitations"] --> B["Data: Experimental & field data on choices"] B --> C["Methodology: Prospect Theory & Cognitive Bias analysis"] C --> D["Computational Process: Heuristic decision modeling"] D --> E["Key Findings: Non-standard utility, systematic deviations, policy implications"]