Cross-Cultural factors and Portfolio Choice

Daniel Egan, Greg Davies, Peter Brooks

Barclays Wealth Behavioural Analytics

FUR Conference

01/07/2008

2

Building Individual Portfolios

Irrational

Cultural

Individual

Circumstantial

How do we interpret and use variation in behaviour and preferences?

?

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Survey and Dataset

UK SG TW HK CN INN= 2,468 353 398 415 443 389 468

Male % 63 51 69 63 71 57Age- mean (sd) 41 (10) 38 (9) 39 (9) 40 (8) 34 (7) 33 (10)

Preliminary filterearned equal to or greater than the top 10th local percentile of income earners reported investable wealth equal to twice the top 10th local percentile of income

SurveySection I - DemographicsSection II - 80 questions relating to investment and personality traits.

All questions in Section II were randomised.English in the UK, Singapore, and IndiaLocal 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

Key Variables

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Risk Tolerance

5

Have to fix order to be consistent!!

Risk Tolerance Score Risk Tolerance Profile

Portfolio Choice

£0

£5,000

£10,000

£15,000

£20,000

£25,000

£30,000

£35,000

£40,000

Portfolio1 Portfolio2 Portfolio3 Portfolio4 Portfolio5

High

Most Likely

Low

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“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

Risk Perception

£0

£5,000

£10,000

£15,000

£20,000

£25,000

£30,000

£35,000

£40,000

High

Most Likely

Low

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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...

Monthly returns Jan 2000 – June 2008

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Return Expectations

9

Classifying expectations Shows what “good” returns are

Excellent

Good

Neither bad

nor good

Poor

Terrible

Bivariate analysis

Predicting Portfolio Choice

10

Risk tolerance

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Portfolio Choices by Risk Tolerance Score

Least risky

Most Risky

** Statistically significant differences in mean portfolio choice across Risk Tolerance Profiles

Risk Perception

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Mean Portfolio Choice by Risk Perception

Higher return expectations do drive riskier choice

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0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Portfolio 1 Portfolio 2 Portfolio 3 Portfolio 4 Portfolio 5

High Expectations

Low Expectations

Responsive Expectations

Middle Expectations

Returns Expectations and Portfolio ChoiceCumulative Choice

Cumulative distribution of each returns expectation profileacross choices of portfolio

Comparative explanatory power

Predicting Portfolio Choice

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Baseline Difference in Portfolio Choice

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UK SG TW HK CN IN

Difference from UK

Allow effect of Risk Tolerance to vary

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UK SG TW HK CN IN SG TW HK CN INUK

Intercepts

Difference from UK Difference from UK

Allow effect of Risk Perception to vary

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UK SG TW HK CN IN SG TW HK CN INUK

Intercepts

Difference from UK Difference from UK

Intercepts

Allow different Returns Expectations

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UK SG TW HK CN IN

Difference from UK

Mod High Resp

All together now!

19

RT

Baseline Main Effects Interactions

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

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Risk Perception not predictive

Except China – negative!

Returns Expectations are! Especially when interacted

with Risk Tolerance

Fin.

21

dd month year

22

Social support network effects perceptions, not choices.

dd month year

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Risk perception and social support Portfolio choice and social support

"If things went wrong financially, I could rely upon the support of my family and friends."

"If things went wrong financially, I could rely upon the support of my family and friends."

dd month year

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dd month year

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A progression of cultural differences

A Similarity index (UK based) reveals an intuitive progression

0.65

0.70

0.75

0.80

0.85

0.90

0.95

1.00

SG TW HK IN CN

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

Two models of the investment decision

multi-attribute representation

allows better comparison of constituent attributes

requires reconciliation into single decision node

dd month year

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Source:

Bottom-upPercieved RiskSocial SupportRecency Bias

Subjective Benefit* Returns Expectations* E([U(X)]

Risk/Return Risk ToleranceRisk PreferenceAffective Appraisal

Portfolio Choice

Objective Risk•Possibility of loss•Mass of loss•Maximum loss* Variance

Objective Benefit* E(X)?•E[U(X)]?•Max(X)?

ProspectivePortfolios

Top-down

affective reaction

non-compensatory

results in transitive preferences

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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 Differences Explanation

Income Risk

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Income Risk? Income Risk

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0%

10%

20%

30%

40%

50%

60%

70%

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

0%

5%

10%

15%

20%

25%

30%

35%

40%

June 2007

March 2008

Down One No Change Up One

Low Med-Low Moderate Med-High High

Return / Volatility Environment

dd month year

30

Social network support

dd month year

31

Risk Tolerance across all locations

dd month year

32

UK SG TW HK CN IN

UK SG TW HK CN IN RTS

Intercepts

Intercepts

Risk Perception

dd month year

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UK SG TW HK CN IN Risk Perception