Behavioral Finance Introduction

• Behavioral Finance is taught by Jim B. Acuzar.

Course Description

• The course covers insights and findings from behavioral finance.
• It studies psychological phenomena influencing investors, analysts, and portfolio managers.
• Short cases are used to convey key points.

Session Objectives: Introduction to Behavioral Finance

• Understand behavioral finance and how it differs from traditional finance.
• Recognize the limitations of traditional finance theories.
• Appreciate the historical development of behavioral finance.

Introduction to Behavioral Finance

• Behavioral finance examines how psychological influences and cognitive biases affect financial decisions.
• Traditional finance assumes investors are rational and markets are efficient.
• Financial decision can be attributed to making irrational financial choices.

Key areas of Behavioral Finance

• Emotions and biases impact investment decisions.
• Markets deviate from rational expectations.
• Psychological factors cause asset bubbles and crashes.

Overview of Traditional Finance and its Limitations

• Investors frequently overreact to market trends.
• Stock market bubbles (e.g., the Dot-com Bubble) contradict the Efficient Market Hypothesis.
• Emotional biases influence investment behavior.

Historical Development of Behavioral Finance

• Prospect Theory (1979), Daniel Kahneman & Amos Tversky details that:
  • People evaluate gains and losses differently, leading to inconsistent decision-making.
  • Losses psychologically hurt more than equivalent gains (loss aversion).

Psychological Biases and Heuristics

• Understand the role of cognitive biases in financial decision-making.
• Identify common financial biases and their real-world impact.
• Recognize how heuristics shape financial behavior.

Understanding Cognitive Biases in Decision-Making

• Cognitive biases are systematic errors in thinking that affect decision-making causing irrational financial choices.
• Brains rely on shortcuts to quickly process information and useful in everyday life.
• Shortcuts can lead to poor financial decisions.

Common Financial Biases

• Overconfidence and Illusion of Control is believing you have more control over outcomes than you actually do.
  • Example: A day trader believes they can consistently beat the market.
• Self-Attribution Bias is attributing success to skill but blaming failures on external factors.
  • Example: An investor blames losses on the economy but credits stock gains to their own skill.
• Hindsight Bias is believing past events were predictable.
  • Example: Claiming "I knew the stock market would crash!" after it happens.
• Confirmation Bias is seeking information that supports pre-existing beliefs.
  • Example: An investor only reading news that confirms a positive view of a stock.
• Narrative Fallacy is believing compelling stories over factual data.
  • Example: Buying stocks based on a CEO's charisma rather than financial reports.
• Representative Bias is making decisions based on stereotypes.
  • Example: Assuming any successful startup will be the next Apple.
• Framing Bias is decisions influenced by how information is presented.
  • Example: Buying a product labeled "90% fat-free" instead of "10% fat".
• Anchoring Bias is relying too heavily on the first piece of information.
  • A stock is valued based on its previous price rather than its actual worth.
• Loss Aversion is fearing losses more than valuing gains.
  • Example: Holding onto a losing stock to avoid realizing a loss.
• Herding Mentality is following the crowd without analysis.
  • Example: Buying Bitcoin just because everyone else is doing it.

Common Heuristics and their Impact

• Heuristics are mental shortcuts people use to make quick decisions and often lead to biases.
• Availability Heuristic is basing decisions on easily recalled events.
  • Example: Investing in a stock because it was recently in the news.
• Affect Heuristic is relying on emotions rather than logic.
  • Example: Buying stocks in a company because you like its brand.
• Representativeness Heuristic is using past patterns to predict future outcomes.
  • Example: Assuming a company will continue to perform well because it has in the past.

Unit 2 Contents

• Prospect Theory
• Overconfidence and Self-Attribution
• Loss Aversion and Regret Aversion

Session Objectives: Introduction to Prospect Theory

• Understand the definition and implications of Prospect Theory.
• Recognize how the theory applies to investment decisions.
• Evaluate critiques and limitations of Prospect Theory.

Prospect Theory

• Key Insights:
  • People evaluate gains and losses differently.
  • Losses hurt more than equivalent gains bring joy (loss aversion).
  • Decisions depend on perceived gains/losses from a reference point (reference dependence).
  • The psychological impact of changes decreases as the amount increases (diminishing sensitivity).
• Implications:
  • Investors tend to avoid selling losing stocks due to loss aversion.
  • Individuals take excessive risks when facing losses (risk-seeking behavior).
  • Framing effects influence financial choices.

Critiques and Limitations of Prospect Theory

• Lack of universality: Different cultures and individuals may not exhibit the same biases.
• Context-dependent: Real-world decisions involve more complexity than simplified lab experiments.
• Contradictions in behavior: Some investors act rationally despite loss aversion.

Introduction to Overconfidence and Self-Attribution: Session Objectives

• Understand how overconfidence manifests in financial markets.
• Recognize the impact of overconfidence on trading behavior.
• Explore self-attribution bias and its consequences.

Exploring Overconfidence in Financial Markets

• Overconfidence is the tendency to overestimate one's knowledge, ability, and control over events.
  • Investors, traders, and fund managers can be overconfident.
• Types of Overconfidence:
  • Overprecision – excessive certainty about predictions.
  • Overplacement – believing one is better than others at investing.
  • Overestimation – exaggerating one's abilities.
• Impact on Trading Behavior and Investment Decisions:
  • Excessive trading – overconfident traders tend to trade too frequently, reducing net returns.
  • Underestimation of risk – investors fail to diversify, assuming they can predict market movements.
  • Bubble formation and market volatility – overconfidence fuels speculative bubbles (e.g., Dot-com Bubble).

Loss Aversion and Regret Aversion: Session Objectives

• Understand loss aversion and its influence on decision-making.
• Recognize regret aversion and its impact on investment choices.
• Analyze risk-taking behavior in the face of losses.

Understanding Loss Aversion

• Losses feel psychologically worse than equivalent gains.
• Investors hold onto losing stocks longer than they should.
• Real-World Impact
  • Endowment Effect – people overvalue things they already own.
  • Stock Market Behavior – investors avoid selling losing stocks due to emotional attachment.

Regret Aversion and its Impact on Investment Strategies

• Definition: Fear of making a wrong decision and experiencing regret; leads to inaction bias
• Examples in Investing:
  • Avoiding selling a stock to avoid feeling regret if it later recovers.
  • Choosing "safer" investments even when riskier ones have higher potential returns.

Risk-Taking Behavior in the Face of Losses

• Investors often take excessive risks after a loss to "break even".
• This leads to "doubling down" on bad investments.
• Behavioral Patterns:
  • Sunk Cost Fallacy – continuing an investment simply because of past losses.
  • Gambler's Fallacy – believing a losing streak will end soon.