1. The optics of risk & return:
How visualizations influence investment decisionsHow visualizations influence investment decisions
Daniel P. Egan
Director of Investing & Behavioral Finance
dan@betterment.com
www.dpegan.com
@daniel_egan
April 2013

2. 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 vs
return
We now have a pretty good
understanding of those
weaknesses…
Make trade-offs clear
Let them experience it
Let them play with it
2

3. 250
300
350
400
450
500
Total 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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4. Perceptions rely on immediate context
4

5. 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 your 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

6. 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

7. Getting invested: Myopic loss aversion
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Source: S&P500 Data from Yahoo

8. Getting invested: Myopic loss aversion
Source: S&P500 Data from Yahoo
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9. 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
9
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

10. Why do I care about a 1 day
change?
Example: Focused on Data, not decisions
What’s the purpose?
Why is it here?
10
Is this important?
Call to action to do
what?

11. Not profiting (psychologically) from diversification
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12. Give the information they want & need
Focus on goals
Give advice on how
to achieve goal
Focus on the big
picture – benefits of
diversification
12

13. 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?

14. Give the information they want & need
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Where do I want to be?
Where am I now?

15. 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
15
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

16. 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
16

17. 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
17

18. “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.”

19. 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
19