1. Volatility – an anomaly?
Michael Fraikin
Head of Portfolio Management
Invesco Global Quantitative Equity
27th of January 2011
This presentation is exclusively for use by
professional clients and financial advisors in
Continental Europe and is not for retail client use.
Please do not redistribute.

2. Table of contents
1. Volatility Anomaly – Theory vs. practice
2. Investment Process – A possible approach
3. Performance – Alpha opportunity in a European context
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3. 1. Volatility Anomaly –
Theory vs. practice

4. Theory:
More risk = more return and the combinations of market and
risk free asset dominates all other portfolio
capital
allocation line
efficient
return
market portfolio
frontier
portfolios
R0
minimum-variance portfolio
risk
CAPM: Capital Asset Pricing Model
R0: risk free rate
For illustration only
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5. What we observe: higher risk is not rewarded
60%
40%
Annualised Return
20%
0%
-20%
-40%
The slope of the regression line is negative!
-60%
0% 10% 20% 30% 40% 50% 60% 70% 80%
Annualised Volatility
Source Bloomberg, Invesco Research, European equities members of the Stoxx 600 over the period 30.06.2002 to 30.06.2010
(8 years). Volatility is calculated as annualised standard deviation of monthly returns.
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6. Highest volatility stocks underperform
10% 100%
Return per decile
9% 90%
8% 80%
Annualised Return
Average Volatility
7% 70%
6% 60%
5% 50%
4% 40%
Volatility per decile
3% 30%
2% 20%
1% 10%
Return (lhs) Volatility (rhs)
0% 0%
1 2 3 4 5 6 7 8 9 10
Volatility Decile
Decile 1 = 10% of stocks in sample with lowest volatility: 8% return p.a. with volatility <20%
Decile 10 = 10% of stocks in sample with highest volatility: 3x the volatility for 1/3 of the return
Source Bloomberg, Invesco Research, European equities members of the Stoxx 600 over the period 30.06.2002 to 30.06.2010
(8 years). Volatility is calculated as annualised standard deviation of monthly returns.
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7. Long-term evidence:
Relative Performance of European Risk Factors
220 220
Momentum
200 Earnings yield 200
Dividend yield
180 Value 180
Liquidity
160 Size 160
Leverage
140 Growth 140
Volatility
120 120
100 100
80 80
60 60
Dez-1994 Dez-1996 Dez-1998 Dez-2000 Dez-2002 Dez-2004 Dez-2006 Dez-2008 Dez-2010
Source Barra, Invesco Research Data from 12/1994 to 12/2010, For illustrative purposes only
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8. Long-term evidence: the world
Minimum Variance MSCI Hedged
Return
1 yr 0.18% 10.32%
3 yr -5.76% -4.94%
5 yr 0.67% 1.34%
10 yr 3.93% 3.09%
30. Apr. 93 7.88% 8.89%
Volatility
1 yr 6.62% 16.09%
3 yr 10.10% 21.05%
5 yr 9.04% 17.14%
10 yr 8.56% 15.72%
30. Apr. 93 8.16% 14.73%
Quelle: MSCI Barra, Invesco Research, 04/1993 bis 12/2010. Based on a simulation of a
minimum-variance portfolio. For illustration only.
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9. Long-term evidence: the world
3 y e a r r o l l i n g r i sk l e v e l s
25%
20%
15%
10%
5%
0%
Dez 96 Dez 97 Dez 98 Dez 99 Dez 00 Dez 01 Dez 02 Dez 03 Dez 04 Dez 05 Dez 06 Dez 07 Dez 08 Dez 09 Dez 10
Mi ni mumVar i ance MSCI Wor l d Hedged
Quelle: MSCI Barra, Invesco Research, 04/1993 bis 12/2010. Based on a simulation of a
minimum-variance portfolio. For illustration only.
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10. Evidence:
More risk does not necessarily mean more return
capital
allocation line
efficient
return
market portfolio
frontier
portfolios
R0
minimum-variance portfolio
risk
CAPM: Capital Asset Pricing Model
R0: risk free return
For illustration only
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11. Possible reasons
• Investment restrictions
— To increase equity market participation some investors may prefer high beta
portfolios effectively circumventing their investment restrictions. The reverse will
not be the case
— High beta seems an easy strategy to outperform a risky asset class
— High beta stocks tend to be small and more difficult to short limiting arbitrage
• Behavioural reasons
— Some investors tend to think in terms of more or less risky asset classes and
may ignore the less volatile, seemingly boring end of a more risky asset class
— Blindly trusting CAPM investors expect high return = high risk and concentrate
on the easier task of forecasting risk
• Lottery effect
— Stocks with high volatility can deliver outsized returns and some investors are
(may be unwittingly) prepared to pay a premium for that
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12. 2. Investment Process –
A possible approach

13. Unconstrained Optimisation: Exit benchmark-orientation
§ Strict risk management
® Limited volatility
® Absolute position limits in terms of stock, sector, country and regional weights
® Liquidity bounds
® Constructing the portfolio with absolute risk aversion
§ Stronger focus on stock selection
® Avoiding unattractive index heavy weights
® High tracking error versus index
® Ability to emphasise attractive stocks1
1 Based on Invesco GQE forecasts
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14. Portfolio Characteristics
§ Diversified portfolio
— Maximum stock position1 2,5%
— Maximum industry weight1 25,0%
§ Selected from a universe of 800 (3300) European (Global) stocks
— Minimum requirements in terms of float and market cap
— Holdings limited to 50% of average daily volume1
§ Expected risk below market risk
— Portfolio beta below 1
§ Fully invested
— No strategic cash
— No short
1 at rebalancing
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15. Quantifying our insights: Stock Selection Model
Stock Selection Universe
Earnings Management
Concepts Price Trend Relative Value
Momentum Action
Are earnings improving What does the market What is management What are the expectations
or deteriorating? movement tell us? telling us? relative to fundamental
measures?
• Estimate Revision • Long-Term Strength • Capital Allocation • Earnings Yield
• Earnings Momentum • Risk-adjusted • Earnings Accruals • Cash Flow Yield
• Revisions Against Relative Strength • Fundamental Health • Dividend Yield
Factors1 Trend • Business Cycle Score
Reversal • Liability Payback
• Short-Term Reversal Horizon
• Volatility Jump • Capital Expenditures
Forecasted Return
For illustrative purposes only
1
Not all factors are used in all regions
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16. Engineering the Optimal Portfolio
Stock Return Stock Risk
Forecasts Forecasts
Transaction Cost Optimization Portfolio Guidelines
Forecast through GPMS1 & Constraints
Final Review
Portfolio
Global Portfolio Management System
1
For illustrative purposes only
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17. Summary
§ Less risk does not necessarily mean less return
§ Combining low volatility and stock selection has generated appealing returns
§ Attractive diversification from both index oriented as well as traditional
fundamental portfolio management
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