analytics in financial services prez behavioral finance + data visualization - visualizing risk...
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The optics of risk & return: How visualizations influence investment decisionsHow visualizations influence investment decisions
Daniel P. Egan
Director of Investing & Behavioral [email protected]
www.dpegan.com@daniel_egan
April 2013
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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
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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
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Getting invested: Myopic loss aversion
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Source: S&P500 Data from Yahoo
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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
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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?
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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?
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Give the information they want & need
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Where do I want to be? Where am I now?
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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
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
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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 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.”
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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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