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Cross-Cultural factors and Portfolio Choice Daniel Egan, Greg Davies, Peter Brooks Barclays Wealth Behavioural Analytics FUR Conference 01/07/2008.

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Presentation on theme: "Cross-Cultural factors and Portfolio Choice Daniel Egan, Greg Davies, Peter Brooks Barclays Wealth Behavioural Analytics FUR Conference 01/07/2008."— Presentation transcript:

1 Cross-Cultural factors and Portfolio Choice Daniel Egan, Greg Davies, Peter Brooks Barclays Wealth Behavioural Analytics FUR Conference 01/07/2008

2 2 Building Individual Portfolios Irrational Cultural Individual Circumstantial How do we interpret and use variation in behaviour and preferences? ?

3 3 Survey and Dataset UKSGTWHKCNIN N= 2,468353398415443389468 Male %635169637157 Age- mean (sd)41 (10)38 (9)39 (9)40 (8)34 (7)33 (10) Preliminary filter earned equal to or greater than the top 10 th local percentile of income earners reported investable wealth equal to twice the top 10 th local percentile of income Survey Section I - Demographics Section II - 80 questions relating to investment and personality traits. All questions in Section II were randomised. English in the UK, Singapore, and India Local script in Hong Kong, Taiwan, and China (PRC) Validation Filter -- Must have taken reasonable time to complete survey -- Must have answered a few questions consistently -not preferring a 5% return over a 20% return or a 15% return. - The total effect was to remove an average 10% of each locations sampled

4 Key Variables 4

5 Risk Tolerance 5 Have to fix order to be consistent!! Risk Tolerance ScoreRisk Tolerance Profile

6 Portfolio Choice 6 “The chart shows the high, low and most likely final values of £12,500 invested in 5 different portfolios for 5 years. For example, in Portfolio 1 you will get £13,500 and in Portfolio 5 you end up getting anything between £7,500 and £34,000, but the most likely amount is £19,000. Which portfolio would you prefer?” Which portfolio would you prefer?No large differences across nations

7 Risk Perception 7 The chart shows the high, low and most likely final values of a £12,500 investment in 5 years. Please rate how risky you think this investment is.” How risky is this investment?That depends...

8 Monthly returns Jan 2000 – June 2008 8

9 Return Expectations 9 Classifying expectationsShows what “good” returns are Excellent Good Neither bad nor good Poor Terrible

10 Bivariate analysis Predicting Portfolio Choice 10

11 Risk tolerance 11 Portfolio Choices by Risk Tolerance Score Least risky Most Risky ** Statistically significant differences in mean portfolio choice across Risk Tolerance Profiles

12 Risk Perception 12 Mean Portfolio Choice by Risk Perception

13 Higher return expectations do drive riskier choice 13 Returns Expectations and Portfolio ChoiceCumulative Choice Cumulative distribution of each returns expectation profile across choices of portfolio

14 Comparative explanatory power Predicting Portfolio Choice 14

15 Baseline Difference in Portfolio Choice 15 UKSGTWHKCNIN Difference from UK

16 Allow effect of Risk Tolerance to vary 16 UKSGTWHKCNINSGTWHKCNIN UK Intercepts Risk Tolerance Difference from UK

17 Allow effect of Risk Perception to vary 17 UKSGTWHKCNINSGTWHKCNIN UK Intercepts Risk Perception Difference from UK

18 Intercepts Returns Expectations Allow different Returns Expectations 18 UKSGTWHKCNIN Difference from UK ModHighResp

19 Intercepts RT * RE All together now! 19 RP RT Baseline Main Effects Interactions

20 Conclusions  Controlling for:  Risk Tolerance;  Risk Perception;  Returns Expectations;  Country-specific effects;  Only China maintains base-level difference in portfolio choice  Risk Tolerance always predictive  Singaporeans more sensitive 20  Risk Perception not predictive  Except China – negative!  Returns Expectations are!  Especially when interacted with Risk Tolerance

21 Fin. 21

22 dd month year 22

23 Social support network effects perceptions, not choices. dd month year 23 Risk perception and social supportPortfolio choice and social support "If things went wrong financially, I could rely upon the support of my family and friends."

24 dd month year 24

25 dd month year 25 A progression of cultural differences A Similarity index (UK based) reveals an intuitive progression  The more mature the economy and market, the more it resembles the UK  The more dislike the UK, the higher the variance of its measurements  Indicates lack of stability in market expectations and understanding

26 Two models of the investment decision multi-attribute representation allows better comparison of constituent attributes requires reconciliation into single decision node dd month year 26 Source: Bottom-up Percieved Risk Social Support Recency Bias Subjective Benefit * Returns Expectations * E([U(X)] Risk/Return Risk Tolerance Risk Preference Affective Appraisal Portfolio Choice Objective Risk Possibility of loss Mass of loss Maximum loss * Variance Objective Benefit * E(X)? E[U(X)]? Max(X)? Prospective Portfolios Top-down affective reaction non-compensatory results in transitive preferences

27 27 What and why are there cultural differences?  Risk Preferences  Risk Perception  Probabilistic Calibration  Trading Behaviour  Overconfidence  Social network support (Weber and Hsee)  Calibration  Base-level risk  Market Maturity (risk/return trade-off)  Utility of Wealth Source: Documented DifferencesExplanation

28 Income Risk 28 Income Risk?Income Risk

29 29 Risk Tolerance  62% of the sample had no change in their allocated Risk Profile over 4 months  No changes of more than 1 Profile  The majority who changed were within 3 points of the profile boundary  The downturn in markets allowed us to test the scales market sensitivity  There was only a minor increase of 1.9% in the “Low” and “Medium- Low” Risk” profiles from June, 2007 Stability Good Risk Tolerance scales are also stable over time, and through market conditions. Risk Tolerance measurements may have some natural variance in them, but not a large amount Testing the Scale Our scales performed extremely well, being stable both across time and changing market conditions. This implies we were measuring a real underlying trait, rather than mood or sentiment Stable Over Time Immune to Market Conditions Down OneNo Change Up One Low Med-Low Moderate Med-High High

30 Return / Volatility Environment dd month year 30

31 Social network support dd month year 31

32 Risk Tolerance across all locations dd month year 32 UKSGTWHKCNIN UKSGTWHKCNINRTS Intercepts

33 Risk Perception dd month year 33 UKSGTWHKCNINRisk Perception


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