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13 October 2009 What QS can learn from Behavioral Finance 1

Behavioral Finance and Risk Management

Guido Baltussen,October 12 th 2009


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Behavioral Finance

The traditional finance paradigm studies finance by(irrationally) assuming all agents are rationaloptimizers.

By contrast, behavioral finance aims at improvingour understanding of the behavior of financialmarkets and its participants, by applying insightsfrom psychology and other behavioral sciences

BF started in 1750s, and it grew rapidly during thelast 10 years.

I will discuss one of the latest insight and its relation

with incentive schemes and risk management


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Summary: irrational risk preferences

Question: How do people respond to losses relativeto a benchmark, or reference point?

To study this data I use date from the televisiongame show Deal or No Deal, which is a perfectnatural laboratory for analyzing decisions thatinvolve risk

I find that people take more risk after losingsubstantial amounts of money

This is inconsistent with the rational (utility-based)models, which form the basis of many incentive

schemes and risk management models.


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Round 1

Mean = 453,326


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Round 2

Mean = 537,602


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Round 3

Mean = 689,911



Round 4

Mean = 947,690



Round 5

Mean = 1,263,583



Round 6: No Deal

Mean = 1,515,300



Round 7

Mean = 1,894,000



Anecdotic evidence?Unlucky Frank

Dutch contestant,aired January 1, 2005



Round 1: No Deal

Mean = 383,427



Round 6: No Deal

Mean = 102,006



Round 9: No Deal

Mean = 5,005



Contestant Frank, NL, Jan 1, 2005



Main findings

Choices are influenced by previous, but irrelevant,outcomes, even with these very large amounts at stake:

People take more risk if they are in a very unfavorable(loser) situation.

This tendency to take more risk after losses holds whileno real losses are at stake, but expected winnings fallshort of (personal) benchmark.



Implications(1)

What does this mean for investments?

People take more risk if they are losing money in an

absolute sense (f.e. day traders)

People take more risk if they are losing money in arelative sense (f.e. fund managers )

More risk taking in markets tend to increase volatility



Implications(2)

Incentive schemes:

Incentive schemes tend to increase risk taking behavior

Since outcomes below benchmark feel as losses, repayschemes may only provide a partial solution

Risk management:

More risk taking after losses increases volatility (risk) ofinvestments, especially after down markets.

Risk management managers should take this dynamicaspect of behavior into account to not misjudge risk.



Summary

People do not behave in accordance with the standard financemodels

Instead, the psyche of investors has substantialconsequences for the behavior and risks of financial markets

Hence, as risk managers be aware of this!



Questions ?



Appendices



Two Theories of Risky ChoiceExpected Utility Theory (John von Neumann and OskarMorgenstern, 1944)

Describes how people should make decisions by means ofrational computations based on objective outcomes and

probabilities, without cognitive limitations and emotions


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Two Theories of Risky ChoiceProspect Theory (Amos Tversky and Daniel Kahneman, 1979)

Describes how people actually make decisions, based on severalanomalies that have been observed in experiments, including- framing in terms of gains of losses- loss aversion- convex value function for losses


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Loser Neutral Winner

Round %BO No. %D %BO No. %D %BO No. %D

1 6% 17 0% 6% 17 0% 6% 17 0%

2 15% 17 0% 12% 17 0% 15% 17 0%

3 40% 17 12% 29% 17 41% 31% 17 6%

4 69% 14 14% 58% 13 46% 54% 14 21%

5 82% 10 10% 71% 10 20% 78% 10 40%

6 94% 8 50% 85% 7 43% 86% 8 63%

7 99% 4 25% 97% 3 67% 99% 4 75%

8 105% 1 0% 91% 3 67% 100% 1 100%

9 120% 1 0% - 0 - 91% 1 100%

2 - 9 72 14% 70 31% 72 25%

Decisions of Losers and Winners

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