Behavioral Finance Course

Lesson 1 • Classical Finance and Its Limits

Examines the efficient market hypothesis and rational agent model as baseline assumptions. Reveals empirical anomalies that classical theory cannot explain, motivating the behavioral approach.

Lesson 2 • Origins of Behavioral Finance

Traces the field's development from psychology research into economic modeling. Connects foundational academic milestones to practical investment implications.

Lesson 3 • Core Psychological Concepts

Introduces heuristics, biases, and dual-process thinking as the psychological engines of irrational behavior. Provides vocabulary used throughout the course.

Lesson 1 • Heuristics and Judgment Shortcuts

Explains availability, representativeness, and anchoring heuristics as mental shortcuts with predictable error patterns. Links each heuristic to specific investment mistakes.

Lesson 2 • Framing, Mental Accounting, and Categorization

Examines how presentation format and mental categorization alter financial choices independently of objective value. Connects framing effects to asset allocation errors.

Lesson 3 • Confirmation and Attribution Biases

Covers selective information processing and self-serving attribution in investment analysis. Shows how these biases reinforce poor decisions and resist correction.

Lesson 4 • Overconfidence and Illusion of Control

Analyzes overconfidence in forecasting, calibration failures, and the illusion of control over random outcomes. Demonstrates how overconfidence inflates trading volume and risk-taking.

Lesson 1 • Mood, Affect, and Financial Judgment

Reviews evidence that ambient mood and incidental affect systematically shift risk tolerance and return expectations. Covers weather, news, and physiological mood proxies.

Lesson 2 • Prospect Theory and Loss Aversion

Presents the value function and probability weighting from prospect theory as the dominant model of risky choice. Quantifies loss aversion coefficients and their portfolio consequences.

Lesson 3 • Fear, Greed, and Market Sentiment

Analyzes how fear and greed cycles amplify price volatility beyond fundamental value. Links investor sentiment indices to predictable return patterns.

Lesson 1 • Bubbles, Manias, and Crash Dynamics

Applies herding and sentiment models to explain asset price bubbles and sudden crashes. Students identify early-warning indicators of bubble formation.

Lesson 2 • Social Influence on Financial Decisions

Examines conformity, social proof, and peer effects as drivers of correlated investor behavior. Distinguishes rational information sharing from irrational imitation.

Lesson 3 • Institutional Herding and Career Concerns

Analyzes how career risk and benchmarking incentives push professional managers toward consensus positions. Links institutional herding to momentum and crowded trades.

Lesson 4 • Information Cascades and Herding Models

Presents formal cascade models showing how private signals are suppressed by observed actions. Students trace cascade formation and fragility conditions.

Lesson 1 • Calendar and Attention-Driven Anomalies

Examines seasonal return patterns and attention-driven buying as evidence of investor irrationality. Links media coverage and search trends to short-term price pressure.

Lesson 2 • Limits to Arbitrage and Mispricing

Explains why rational arbitrageurs cannot fully eliminate mispricing due to noise trader risk and capital constraints. Establishes the theoretical foundation for persistent anomalies.

Lesson 3 • Value, Growth, and Investor Sentiment

Analyzes the value premium through the lens of extrapolation bias and investor overreaction to growth. Connects sentiment cycles to value-growth return spreads.

Lesson 4 • Momentum and Reversal Anomalies

Documents short-term momentum and long-term reversal patterns and links them to underreaction and overreaction biases. Students test momentum strategies on historical data.

Lesson 1 • Failures of Mean-Variance Optimization

Identifies how estimation error, loss aversion, and mental accounting cause investors to deviate from mean-variance efficient portfolios. Motivates behavioral alternatives.

Lesson 2 • Behavioral Portfolio Theory Framework

Presents Shefrin and Statman's layered portfolio model where investors hold separate mental accounts for safety and aspiration goals. Contrasts with efficient frontier logic.

Lesson 3 • Behavioral Factors in Factor Investing

Examines how behavioral biases underpin factor premiums such as value, momentum, and low volatility. Students assess factor exposure through a behavioral lens.

Lesson 4 • Goal-Based Investing in Practice

Translates goal-based theory into client portfolio construction steps, matching assets to specific financial goals. Covers goal prioritization and funding status monitoring.

Lesson 1 • Advisor-Client Behavioral Dynamics

Examines how advisor biases interact with client biases to amplify or dampen decision errors. Develops communication strategies that reduce bias-driven conflict.

Lesson 2 • Monitoring and Feedback Systems

Designs ongoing monitoring frameworks that provide investors with bias-relevant feedback loops. Covers performance attribution framing and behavioral scorecards.

Lesson 3 • Behavioral Investor Profiling

Introduces structured frameworks for classifying investors by dominant behavioral tendencies and risk attitudes. Covers questionnaire design and interview techniques for bias elicitation.

Lesson 4 • Nudge Design for Financial Decisions

Applies choice architecture principles to design nudges that steer investors toward better outcomes without restricting choice. Covers default settings, framing, and commitment devices.

Lesson 1 • Behavioral Finance in Corporate Decisions

Extends behavioral analysis to corporate capital allocation, M&A overconfidence, and managerial hubris. Links CEO behavioral tendencies to firm-level financial outcomes.

Lesson 2 • Behavioral Alpha and Strategy Design

Frames exploiting systematic investor biases as a source of alpha in active management. Students design strategies that harvest behavioral mispricings with disciplined execution.

Lesson 3 • Behavioral Risk Management

Integrates behavioral biases into enterprise risk frameworks, identifying how cognitive errors amplify tail risks. Develops bias-adjusted stress testing and scenario analysis.

Lesson 4 • Building a Behavioral Finance Program

Guides students in designing an organization-wide behavioral finance integration program covering training, process redesign, and measurement. Produces a capstone implementation roadmap.