The optics of risk & return: How visualizations influence investment decisionsHow visualizations influence investment decisions

Daniel P. Egan

Director of Investing & Behavioral Financedan@betterment.com

www.dpegan.com@daniel_egan

April 2013

If you remember anything from this talk..

� Most investors make mistakes which cost them real money

� These mistakes are due to specific weaknesses we have in deciding about risk vs

� Focus on the future

� Do the math for them

� Avoid narrow framing

� Make trade-offs clear

Background Solutions

in deciding about risk vsreturn

� We now have a pretty good understanding of those weaknesses…

� Make trade-offs clear

� Let them experience it

� Let them play with it

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250

300

350

400

450

500Total Return (buy and hold strategy)

Investor Return (actual investor returns)

The Behavior Penalty= 1.2% per year†

minus

The cost of bad behavior

0

50

100

150

200

Jan-87 Jan-90 Jan-93 Jan-96 Jan-99 Jan-02 Jan-05 Jan-08 Jan-11†Source: Study commissioned by Barclays Wealth at Cass Business School, Clare & Motson (2010) Do UK retail investors buy at the top and sell at the bottom?; UK equity funds from 1992 to 2009 recorded by the Investment Management Association

Total Return $430,000

Investor Return $360,000

Behavior Penalty $ 70,000

$100,000 compounded over 24 years…

- 16%

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Perceptions rely on immediate context

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Simple investment framing

Alternative A� Recover $2,000

Alternative X� Lose $4,000

Would you choose A or B?

Imagine that you bought $6,000 worth of stock from a now bankrupt

company. There are two alternatives to recover you r money…

Would you choose X or Y?

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� Recover $2,000

Alternative B� 1/3 chance $6,000 recovered� 2/3 nothing recovered

92% go for A

� Lose $4,000

Alternative Y� 1/3 chance nothing lost� 2/3 chance $6,000 lost

67% go for X

Source: Wang, 1996

We’re not good at math (especially compounding)

Imagine you saved $200 a month for 20 years in an account which had an annual interest rate of 5%. How much would you have after 20 years?

Source: McKenzie and Liersch, (2011)

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$81,491

Getting invested: Myopic loss aversion

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Source: S&P500 Data from Yahoo

Getting invested: Myopic loss aversion

Source: S&P500 Data from Yahoo

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Framing of investment decisions: myopia and the emotional time horizon

� Historic Stock Gains: 59%Losses: 41%

� Historic Stock Gains: 74%Losses: 26%

Monthly Observation Annual Observation

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� Loss averse people will avoid stocks due to short-term emotional responses

� Loss aversion kicks in far less frequently so long term goals achieved more easily

A sequence of appropriate short-term decisions do not add up to a good long-term decision

Source: Betterment Analysis, S&P500 data 1954 to 2013

Why do I care about a 1 day change?

Example: Focused on Data, not decisions

What’s the purpose? Why is it here?

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Is this important?

Call to action to do what?

Not profiting (psychologically) from diversification

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Give the information they want & need

Focus on goals

Give advice on how to achieve goal

Focus on the big picture – benefits of diversification

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Give the information they want & need

How do I get from A to B?

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Where do I want to be?

Where am I now?

Give the information they want & need

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Where do I want to be? Where am I now?

Individuality: Can we predict “Nudgeability”?

Experiments show that we can reduce Myopic Loss Aversion by “broad framing”: showing outcomes in bundles (e.g. 365 days worth of outcomes) rather than individual ones.

50

60

70 Amount Invested

Percent of Portfolio Invested in risky asset

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Source: van der Heijden, Klein, Muller and Potters, 2011, Nudges and Impatience: Evidence from a large scale experiment

0

10

20

30

40

Narrow Frame Broad Frame

Individuality: Can we predict “Nudgeability”?

Experiments show that we can reduce Myopic Loss Aversion by “broad framing”: showing outcomes in bundles (e.g. 365 days worth of outcomes) rather than individual ones.

50

60

70 Amount InvestedPatientImpatient

Percent of Portfolio Invested in risky asset

Source: van der Heijden, Klein, Muller and Potters, 2011, Nudges and Impatience: Evidence from a large scale experiment

0

10

20

30

40

Narrow Frame Broad Frame

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Individuality: Can we predict “Nudgeability”?

Experiments show that we can reduce Myopic Loss Aversion by “broad framing”: showing outcomes in bundles (e.g. 365 days worth of outcomes) rather than individual ones.

50

60

70 Amount Invested

Patient

Impatient

Percent of Portfolio Invested in risky asset

Source: van der Heijden, Klein, Muller and Potters, 2011, Nudges and Impatience: Evidence from a large scale experiment

0

10

20

30

40

Narrow Frame Broad Frame

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“In other words, the decision frames of impatient people are affected more easily than those of patient people.

This is interesting … as nudges are typically proposed for individuals with “problematic”

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proposed for individuals with “problematic” behaviors such as low savings, overspending on credit cards, obesity, which have all been associated to a high rate of discounting.”

If you remember anything from this talk..

� Humans are not computers

� We have specific strengths & weaknesses when making decisions about risk & return

� Focus on the future

� Do the math for them

� Avoid narrow framing

� Make trade-offs clear

Background Solutions

� We now have a pretty good understanding of those strengths & weaknesses…

� Make trade-offs clear

� Let them experience it

� Let them play with it

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