INVESTOR BEHAVIOUR

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INVESTOR BEHAVIOUR AND BENCHMARKS Presentation
to Finansmarkedsfondet Executive Board Sari
Carp Norwegian School of Management (BI) 8
December 2005
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PART I Background on Behavioural Finance
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Isaac Newton (losing investor in the South Sea
Bubble) I can calculate the motions of the
heavenly bodies, but not the madness of people.
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• Three Viewpoints on Market Efficiency
• (borrowed from Richard Thaler)
• Efficient Market Zealot (vanishing breed)
• Security prices are always equal to intrinsic
  value.
• Price movements are random, and hence
  unpredictable.
• Behavioural Finance Zealot (figment of EMZs
  imaginations)
• Prices depend only on market psychology.
• It is easy to predict price movements.
• Sensible Middle Ground (nearly everyone)
• Prices are highly correlated with intrinsic
  value, but sometimes diverge significantly.
• It is sometimes possible to predict prices, but
  generally not with great precision.

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The Development of Behavioural Finance Research

• Documentation of anomalies
• Theory building Economics Psychology
• Testing of theories
• Experimental
• Empirical

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Bounded Rationality
? Decision Making Rules Heuristics
? Biases
? Market Imperfections Anomalies
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PART II Investor Behaviour and Benchmarks
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Psychology of Benchmarking

• Fundamental human desire to evaluate ones own
  abilities
• Cannot assess abilities directly, so evaluate the
  result of abilities i.e., performance
• Even if performance can be measured unambiguously
  (e.g. time to run a race), how do we know if its
  good?
• compare with others times
• If an objective, non-social criterion exists,
  then evaluation relative to others is not used
• Focus on a reference point, or goal, decreases as
  the difference between it and ones own ability
  increases

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Antecedents

• Prospect Theory (Kahneman and Tversky, 1979)

• ascribes value to gains and losses, not total
  wealth
• decision makers are risk averse in gains, risk
  seeking in losses
• pain of loss is sharper than pleasure of gain

• March and Shapira, 1992

• two reference points aspiration and survival
• decision makers tolerate high risk when resources
  are below reference point, lower risk when
  resources are above reference point
• decision makers focus only on one of two
  reference points at a time

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Model of Investor Risk Behaviour

• Performance (return) evaluated relative to two
  benchmarks
• Success (S)
• Exit (X)
• In each period, investors choose portfolio risk
  according to
• benchmark(s) focused on
• distance from focal benchmark(s)

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Timeline
time 2 portfolio values change again Success and
Exit benchmark returns also change investors
restrategize based on new values
time 0 portfolios homog. in value,
variance heterog. in assets
time 1 portfolio values change according to
random walk investors choose risk strategies
based on own returns relative to Success and Exit
levels
time t evaluation period ends investors
performing below Exit are eliminated from the
market all others may invest again
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Risk Taken Relative to Performance Benchmarks
Success Focus Exit Focus Mixed Focus
Risk
X
S
Performance (Cumulative Return)
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Risk Taken Relative to Performance Benchmarks
Risk
X
S
Performance (Cumulative Return)
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Mutual Fund Manager Data

• Offshore
• 787 funds (Datastream)
• 25 countries
• all equity
• 1993-2002

• U.S.
• 7,606 funds (CRSP)
• equity and bond
• 2001-2002

• actively managed (no index funds)
• single country focus

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Results from Fund Manager Data

• Results support model highly statistically
  significant
• Model holds across economic, political and legal
  contexts
• Buthow can we know if benchmarking is driven by
  behavioural or compensation based factors??
• By comparing individual and institutional
  investors, we can factor out the compensation
  based element

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VPS Data

• Unique in the world
• Gold mine for behavioural research!!!
• Some behavioural research has been done on
  similar databases from other Scandinavian
  countriesbut, these databases are incomplete
• Very famous behavioural research has been done on
  an individual investor database from a U.S.
  brokerage firmbut, this database is both
  incomplete and biased

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VPS Data

• Complete database of ownership in Norwegian stock
  market
• 10 years of monthly portfolios for each investor
• Investors categorized as individual, financial
  institution, non-financial corporation,
  government or foreign investor
• Tracks each investor by ID over time, allowing
  comparisons of investment decisions under same
  conditions
• Eliminates sample bias

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Predicted Results on VPS Data

• Both professionals and individuals will take
  increased risk as their performance improves
  above the Success or Exit points this result
  will be more pronounced for professionals
• Both groups will take increased risk as
  performance deteriorated below Success or Exit
  points this result will also be more pronounced
  for professionals
• So, the pattern will be the same, but more
  extreme for professionals