Analytics in financial services prez behavioral finance + data visualization - visualizing risk and return

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  • 1. The optics of risk & return:How visualizations influence investment decisionsHow visualizations influence investment decisionsDaniel P. EganDirector of Investing & Behavioral Financedan@betterment.comwww.dpegan.com@daniel_eganApril 2013
  • 2. If you remember anything from this talk..Most investors make mistakeswhich cost them real moneyThese mistakes are due tospecific weaknesses we havein deciding about risk vsFocus on the futureDo the math for themAvoid narrow framingMake trade-offs clearBackground Solutionsin deciding about risk vsreturnWe now have a pretty goodunderstanding of thoseweaknesses…Make trade-offs clearLet them experience itLet them play with it2
  • 3. 250300350400450500Total Return (buy and hold strategy)Investor Return (actual investor returns)The Behavior Penalty= 1.2% per year†minusThe cost of bad behavior050100150200Jan-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?; UKequity funds from 1992 to 2009 recorded by the Investment Management AssociationTotal Return $430,000Investor Return $360,000Behavior Penalty $70,000$100,000 compounded over 24years…- 16%3
  • 4. Perceptions rely on immediate context4
  • 5. Simple investment framingAlternative ARecover $2,000Alternative XLose $4,000Would you choose A or B?Imagine that you bought $6,000 worth of stock from a now bankruptcompany. There are two alternatives to recover your money…Would you choose X or Y?5Recover $2,000Alternative B1/3 chance $6,000 recovered2/3 nothing recovered92% go for ALose $4,000Alternative Y1/3 chance nothing lost2/3 chance $6,000 lost67% go for XSource: 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 anannual interest rate of 5%. How much would you have after 20 years?Source: McKenzie and Liersch, (2011)6$81,491
  • 7. Getting invested: Myopic loss aversion7Source: S&P500 Data from Yahoo
  • 8. Getting invested: Myopic loss aversionSource: S&P500 Data from Yahoo8
  • 9. Framing of investment decisions: myopia and the emotionaltime horizonHistoric Stock Gains: 59%Losses: 41%Historic Stock Gains: 74%Losses: 26%Monthly Observation Annual Observation9Loss averse people will avoidstocks due to short-termemotional responsesLoss aversion kicks in far lessfrequently so long term goalsachieved more easilyA sequence of appropriate short-term decisions do notadd up to a good long-term decisionSource: Betterment Analysis, S&P500 data 1954 to 2013
  • 10. Why do I care about a 1 daychange?Example: Focused on Data, not decisionsWhat’s the purpose?Why is it here?10Is this important?Call to action to dowhat?
  • 11. Not profiting (psychologically) from diversification11
  • 12. Give the information they want & needFocus on goalsGive advice on howto achieve goalFocus on the bigpicture – benefits ofdiversification12
  • 13. Give the information they want & needHow do I get from A to B?13Where do I want to be?Where am I now?
  • 14. Give the information they want & need14Where 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”: showingoutcomes in bundles (e.g. 365 days worth of outcomes) rather than individual ones.506070 Amount InvestedPercent of PortfolioInvested in riskyasset15Source: van der Heijden, Klein, Muller and Potters, 2011, Nudges and Impatience:Evidence from a large scale experiment010203040Narrow Frame Broad Frame
  • 16. Individuality: Can we predict “Nudgeability”?Experiments show that we can reduce Myopic Loss Aversion by “broad framing”: showingoutcomes in bundles (e.g. 365 days worth of outcomes) rather than individual ones.506070 Amount InvestedPatientImpatientPercent of PortfolioInvested in riskyassetSource: van der Heijden, Klein, Muller and Potters, 2011, Nudges and Impatience:Evidence from a large scale experiment010203040Narrow Frame Broad Frame16
  • 17. Individuality: Can we predict “Nudgeability”?Experiments show that we can reduce Myopic Loss Aversion by “broad framing”: showingoutcomes in bundles (e.g. 365 days worth of outcomes) rather than individual ones.506070 Amount InvestedPatientImpatientPercent of PortfolioInvested in riskyassetSource: van der Heijden, Klein, Muller and Potters, 2011, Nudges and Impatience:Evidence from a large scale experiment010203040Narrow Frame Broad Frame17
  • 18. “In other words, the decision frames ofimpatient people are affected more easily thanthose of patient people.This is interesting … as nudges are typicallyproposed for individuals with “problematic”18proposed for individuals with “problematic”behaviors such as low savings,overspending on credit cards, obesity, whichhave all been associated to a high rate ofdiscounting.”
  • 19. If you remember anything from this talk..Humans are not computersWe have specific strengths &weaknesses when makingdecisions about risk & returnFocus on the futureDo the math for themAvoid narrow framingMake trade-offs clearBackground SolutionsWe now have a pretty goodunderstanding of thosestrengths & weaknesses…Make trade-offs clearLet them experience itLet them play with it19