Michael Fraikin

Head of Portfolio Management

Invesco Global Quantitative Equity

27th of January 2011

Volatility – an anomaly?

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.

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Table of contents

1. Volatility Anomaly – Theory vs. practice

2. Investment Process – A possible approach

3. Performance – Alpha opportunity in a European context

1. Volatility Anomaly –Theory vs. practice

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Theory:More risk = more return and the combinations of market and risk free asset dominates all other portfolio

risk

retu

rn

portfolios

capitalallocation line

efficient frontier

R0

CAPM: Capital Asset Pricing Model

R0: risk free rate

For illustration only

minimum-variance portfolio

market portfolio

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-60%

-40%

-20%

0%

20%

40%

60%

0% 10% 20% 30% 40% 50% 60% 70% 80%

Annualised Volatility

Annual

ised

Ret

urn

What we observe: higher risk is not rewarded

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.

The slope of the regression line is negative!

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Highest volatility stocks underperform

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.

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

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

10%

1 2 3 4 5 6 7 8 9 10

Volatility Decile

Annual

ised

Ret

urn

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Ave

rage

Vol

atili

ty

Return (lhs) Volatility (rhs)

Return per decile

Volatility per decile

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Long-term evidence:Relative Performance of European Risk Factors

Source Barra, Invesco Research Data from 12/1994 to 12/2010, For illustrative purposes only

60

80

100

120

140

160

180

200

220

Dez-1994 Dez-1996 Dez-1998 Dez-2000 Dez-2002 Dez-2004 Dez-2006 Dez-2008 Dez-2010

60

80

100

120

140

160

180

200

220Momentum

Earnings yield

Dividend yield

Value

Liquidity

Size

Leverage

Growth

Volatility

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Long-term evidence: the world

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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Minimum Variance MSCI Hedged

Return1 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%

Volatility1 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%

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Long-term evidence: the world

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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3 y e a r r ol l i ng r i sk l e v e l s

0%

5%

10%

15%

20%

25%

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

Minimum Var iance MSCI Wor ld Hedged

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Evidence:More risk does not necessarily mean more return

risk

retu

rn

portfolios

capitalallocation line

efficient frontier

R0

CAPM: Capital Asset Pricing Model

R0: risk free return

For illustration only

minimum-variance portfolio

market portfolio

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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 concentrateon 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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2. Investment Process –A possible approach

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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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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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Quantifying our insights: Stock Selection Model

ManagementAction

EarningsMomentum Relative ValuePrice Trend

Forecasted Return

• Capital Allocation• Earnings Accruals• Fundamental Health

Score• Liability Payback

Horizon• Capital Expenditures

• Estimate Revision• Earnings Momentum• Revisions Against

Trend

• Long-Term Strength• Risk-adjusted

Relative Strength• Business Cycle

Reversal• Short-Term Reversal• Volatility Jump

Concepts

Factors1

• Earnings Yield • Cash Flow Yield• Dividend Yield

For illustrative purposes only 1Not all factors are used in all regions

What are the expectationsrelative to fundamental measures?

Are earnings improving or deteriorating?

What does the marketmovement tell us?

What is management telling us?

Stock Selection Universe

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Engineering the Optimal Portfolio

Final Review

Stock RiskForecasts

Stock ReturnForecasts

Portfolio

Optimization through GPMS1

Transaction CostForecast

Portfolio Guidelines& Constraints

1Global Portfolio Management SystemFor illustrative purposes only

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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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• This marketing document is exclusively for use by professional clients and financial advisors in Netherlands and is not for retail client use. Please do not redistribute. Data as at 31 December 2010, unless otherwise stated.

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