Risk profiling & asset allocationdiscussing risk with clients Phil Simmonds, Head of Intermediary SalesRobert Jukes, Global StrategistCollins Stewart Wealth Management

Safety in numbers

• Our industry is often criticised for positioning onto benchmark at times of market stress – reducing client risk – safety in numbers

• Our industry often criticises its clients for having an inconsistent approach to risk – happy to be aggressive when markets are rising – no risk appetite when they are falling

• We’ve listened, and are now offering a discretionary service that manages money in the way our clients want it managed

• Safety in numbers doesn’t mean running with the herd

The adviser’s conundrum

• Assessment of client risk appetite is a core responsibility

• This will change throughout the client’s lifetime

• Due diligence in selecting appropriate manager to ensure risk appetite is matched

• ….as market cycles evolve, does the risk profile remain constant?

Traditional benchmarks are not working

APCIMs (Inc, Bal & Grow th)

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

0% 1% 2% 3% 4% 5% 6% 7% 8% 9% 10% 11% 12% 13% 14% 15%

APCIMs (Inc, Bal & Grow th)

Risk

Retu

rn

7. 6. 5. 4. 3.2. 0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

0% 1% 2% 3% 4% 5% 6% 7% 8% 9% 10% 11% 12% 13% 14% 15%

New benchmarks

Risk

Retu

rn

7. 6. 5. 4. 3.2.

• APCIMS benchmarks are not evenly spread across the risk curve…

• …partly because they are not risk rated – they reflect return objectives

• A steeper, well spread out model/benchmark offering along the risk / return space ensures appropriate solutions…

• We offer risk rated solutions

Communicating risk to your clients

• Risk = annualised standard deviation of returns

• We need to convey that in a non-mathematical way – keying into our clients own experiences

Solution: REMAPA series of portfolios managed via an enhanced risk framework, which, using a proprietary Market Stress Indicator, properly accounts for rising volatility and correlation. That, combined with a strong research platform, combine to produce a range of evenly spread, multi-asset portfolios that remain within dedicated risk tolerances by seeking to cap volatility.

•REMAP is a robust, intellectually defensible framework that makes better useof active risk

•It addresses the major shortcomings of traditional risk management processes (Modern Portfolio Theory)

•It systematically respects the strict observance of client risk tolerances

•By combining the risk framework with our existing Asset Allocation output and strong bottom-up research capabilities, REMAP aims to grow our clients’ wealth, whilst focusing on capital preservation

•A true multi-asset approach that caps volatility using an independent, open-architecture investment approach

REMAP: Performance

• Strong Risk-adjusted performance last year and into this year

• Maximum portfolio downside through 2011 was 4%, compared with 11% for APCIMS Balanced benchmark

• REMAP Portfolio #5 returned 4.8% vs -0.4% for APCIMS Balanced

90

92

94

96

98

100

102

104

106

108

110

10/01/2011 10/05/2011 10/09/2011 10/01/2012 10/05/2012

REMAP #5

APCIMS Balanced

0%

2%

4%

6%

8%

10%

12%

14%

REMAP #5 CSWM risk-aligned b/m APCIMS Balanced

Total return

Volatility, annualised sd

Volatility cap

REMAP: Performance – with backtesting

• Drawdowns are significantly lower than the benchmark, and the optimised portfolio spends significantly less time below water

• Optimised Balanced Portfolio: 7% Dot Com, 6% Credit Crunch;

• APCIMS Balanced: 35% Dot Com, 30% Credit Crunch

100

150

200

250

300

350

400

450

500

-50%

-45%

-40%

-35%

-30%

-25%

-20%

-15%

-10%

-5%

0%

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Drawdown

REMAP #5

100

150

200

250

300

350

400

450

500

-50%

-45%

-40%

-35%

-30%

-25%

-20%

-15%

-10%

-5%

0%

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Drawdown

APCIMS Balanced

The secret of success #1: avoid the losses

• Managers do not make appropriate use of active risk budgeting relative to benchmarks

• Using the MSCI we can see meaningful outperformance is about avoiding worst periods of negative returns

• By committing to a fixed absolute risk target, we can meaningfully de-risk relative to benchmark in times of market stress

• This ‘Boldly Cautious’ approach is a key characterisation of REMAP

400

900

1400

1900

2400

2900

3400

3900

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

MSCI world ($)

Excluding 10 best weeks

Excluding 10 worst weeks

400

900

1400

1900

2400

2900

3400

3900

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 20110%

5%

10%

15%

20%

25%

30%

35%Active Risk, rhs

Excluding 10 worst weeks

MSCI world ($)

The secret of success #2: avoid high risk returns and compound small gains

-4.0% -3.0% -2.0% -1.0% 0.0% 1.0% 2.0% 3.0% 4.0%

Freq

uenc

y

Weekly return

REMAP #4

APCIMS IncomeMore small positive outcomes clustered around the mean return

Decreased tail risk: fewer extreme values

Average weekly return a little higher and more frequently achieved• Fixing absolute risk also

forces us to focus on lower risk returns.

• Our optimised investment process reduces the ‘fat-tails’ of benchmark portfolio returns (kurtosis)

• This ‘Boldly Cautious’ approach is a key characterisation of REMAP

A boldly cautious approach

• The long-run risk of a client’s benchmark should be aligned to her risk tolerance

• But even the best benchmarks cease to be efficient during periods of market stress

• Managers that simply collapse on to the benchmark asset allocation in times of stress are not doing their job

• REMAP’s ‘boldly cautious’ approach together with its ability to properly account for risk in all market conditions ensures that volatility is capped and client capital preserved

3%

5%

7%

9%

11%

13%

15%

17%

19%

Jun-98 Jun-00 Jun-02 Jun-04 Jun-06 Jun-08 Jun-10

Rolling 2yr volatility, APCIMs balanced benchmark

Client risk tolerance = long run volatility of benchmark

3%

5%

7%

9%

11%

13%

15%

17%

19%

Jun-98 Jun-00 Jun-02 Jun-04 Jun-06 Jun-08 Jun-10

Rolling 2yr volatility, REMAP #5

Client risk tolerance = long run volatility of benchmark

An Endorsement

“In this white paper, I investigate the Collins Stewart Wealth Management (CSWM) risk

model, developed by Robert Jukes and Edward Smith, in the light of academic research and best practise. In particular, my purpose is to assess its ability to

deal with current market turbulence and its usefulness in contributing to

informed investment decisions, especially in the area of asset allocation. I find

that their intuitive framework is one that can be explained to interested clients with

relative ease due to its methodological transparency. That is most important in the current investment environment, which is, legitimately in my view, suspicious of “black box” approaches. For many years wealth

management has rather avoided the use of any mathematics in designing

investment processes. This has now changed and the industry is gradually becoming more aligned with other forms of quantitative asset management; it is pleasing to see

CSWM leading the field rather than following it.”S.E.Satchell

Fellow, Trinity College, Cambridge

The primary failing of MPT I• A failure to adequately address non-constant correlations caused many risk models

to fail in 2008

• As the credit crunch demonstrated, when risk assets deliver unusually large negative returns, they tend to become significantly more positively correlated with other riskassets with which they may not normally have a strong relationship

• Unless we recognise that asset correlations change in times of market stress, it willnot be possible to achieve a well diversified portfolio when such stress occurs

The primary failing of MPT II

•Modern portfolio theory dictates that investors should maximise portfolio return within a given level of risk

•Risk in a multi-asset portfolio is a function of the volatility of the individual holdings as well as their correlation

•If a risk model fails to account for the dramatic changes to volatility and correlation in times of market stress, managers could grossly underestimatethe amount of risk in their clients portfolios when such stress occurs…

•…breach client risk tolerance mandates…

•…and therefore expose their clients to far greater risk of capital loss

Investment Process• A methodologically transparent framework

• Leverages our long term, award winning expertise in Portfolio Management

• Asset allocation driven investment process

• Bottom-up stock, bond and fund research

• Longstanding use of Alternatives provides for a true multi-asset approach

Investment Philosophy

•Our philosophy is founded upon four central principles, around which all investment decisions are based:

•We aim to grow our clients’ wealth, but with a focus on capital preservation.

•We look to avoid the losses and benefit from the compounding effect of small, lower risk, positive gains.

•We believe our job is to manage portfolios more efficiently than ever, in line with clients’ stated risk profiles, in order to maximiserisk-adjusted returns.

•We believe that asset allocation is the main driver of investment returns.

REMAP: A different approach to a major competitor: REMAP 4 case study I

• In the first week of August 2011, equity markets recorded one of the biggest weekly losses on record – over 10%

• Thanks to our focus on capping risk and our ability to measure risk dynamically, properly accounting for nonconstant volatility and correlation, we were already significantly underweight risk-assets on the first of the month (just 13% in prop, oil and equity)

• As out market stress indicator flashed 5 for maximum stress, we allocated all assets of bonds and cash – the only way to cap risk

• The competitor’s portfolio however remained almost identical to the benchmark – causing a major breach of the risk mandate

-2%

0%

2%

4%

6%

8%

10%

12%

Cazenove REMAP

Alternatives

Equities

Bonds

11.2%

5.3%Volatility cap

Contribution to total portfolio risk (ex-ante)Broad asset allocation – August 2011

95%

5%

Bonds

Equities

Alternatives

Cash

REMAP

37%

52%

7%4%

Bonds

Equities

Alternatives

Cash

CazenoveCompetitor A

REMAP: A different approach to a major competitor: REMAP 4 case study II

• In asset allocation, the competitor portfolio is virtually unchanged today versus August last year

• Is the world really the same?

• We still believe that the competitor portfolio is breaching the risk mandate

-2%

0%

2%

4%

6%

8%

10%

12%

Cazenove REMAP

Alternatives

Equities

Bonds

10.3%

5.2%Volatility cap

Broad asset allocation – July 2012 Contribution to total portfolio risk (ex-ante)

68%

13%

8%

12%

Bonds

Equities

Alternatives

Cash

REMAP

34%

53%

10%3%

Bonds

Equities

Alternatives

Cash

CazenoveCompetitor B

Conclusions

•Outsourced DPM solution that strictly observes clients’ risk tolerances

•Seven risk-rated portfolios designed to provide for improved risk-adjusted returns

•Market-leading mathematical framework that complements CSWM’s research and Asset Allocation experience

•Risk framework that addresses the fundamental flaws in more traditional risk management tools

•A focus on capital preservation means taking a boldly cautious approach: avoiding the losses and compounding the gains

•A true multi-asset approach that caps volatility using an independent, open-architecture investment approach

Appendix

REMAP: Performance overview• Significant and consistent risk-adjusted outperformance versus APCIMS universeRisk & return Absolute returnsSince inception 10/01/11 Benchmark Since inception 10/01/11 Benchmark

ModelAPCIMS Balanced

CSWM risk-aligned Model

APCIMS equivalent

CSWM risk-aligned

REMAP #6 Annualised volatility 8% 14% 14% REMAP #6 Since Inception 4.9% 3.4% 5.3%

Sharpe ratio 0.4 0.2 0.3 Last Month 1.1% 1.3% 1.4%

M2 6% 4% 5% Last 3m 4.2% 5.9% 6.2%

Maximum loss -8% -13% -13%

REMAP #5 Annualised volatility 6% 12% 10% REMAP #5 Since Inception 8.3% 5.9% 7.7%

Sharpe ratio 0.8 0.4 0.5 Last Month 1.3% 1.2% 1.1%

M2 8% 4% 5% Last 3m 4.3% 5.3% 5.2%

Maximum loss -6% -11% -9%

REMAP #4 Annualised volatility 4% 9% 6% REMAP #4 Since Inception 10.9% 8.9% 9.9%

Sharpe ratio 1.5 0.6 0.9 Last Month 0.8% 1.0% 0.9%

M2 9% 4% 6% Last 3m 2.4% 4.6% 4.2%

Maximum loss -3% -8% -5%

REMAP #3* Annualised volatility 3% 6% 3% REMAP #3* Since Inception 12.1% 12.1% 7.7%

Sharpe ratio 4.2 2.0 2.5 Last Month 0.7% 0.6% 0.6%

M2 13% 6% 8% Last 3m 2.5% 3.1% 2.4%

Maximum loss -1% -4% -3%

Breached risk capBest performance

Explaining risk to clients• The primary objective of REMAP is to cap risk at a given tolerance level…

• …but does risk/volatility, as expressed by the standard deviation mean anything to a client?

• REMAP #4 aims to cap risk at a standard deviation of 6%. To help put this into context, if we assume a long term return of 6% per year for the portfolio then, in this example, we would expect 95% of future annual returns to be in the range of -6% and 18%...

• or +/- 2x the standard deviation Aiming to cap risk works when you can account for it properly A benchmark oriented approach leads to wilder swings

-18%

-12%

-6%

0%

6%

12%

18%

24%

30%

Jul-97 Jul-99 Jul-01 Jul-03 Jul-05 Jul-07 Jul-09 Jul-11

REMAP #4, rolling 12m return

+/- 2 standard deviations

-18%

-12%

-6%

0%

6%

12%

18%

24%

30%

Jul-97 Jul-99 Jul-01 Jul-03 Jul-05 Jul-07 Jul-09 Jul-11

APCIMS peergroup, rolling 12m return

+/- 2 standard deviations

Rising Portfolio Risks• Multi asset portfolio risk has been rising over the past 30 years, but our client risk tolerance almost certainly has not

• Rising portfolio risk has largely been a function of rising correlations…

• …it’s much harder to provide well diversified portfolios today, than back in the 1980s

• This presentation sets out to explain the concepts that make the link between portfolio volatility and asset correlation

Rising portfolio risk… ….caused by rising correlations

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010

Portfolio (30% US equities; 30% foreign eq'; 25% USbonds; 10 property; 5% commodities) - annualisedsd

Linear trend

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010

World ex US equities (USD)

Copper

US Property

Asset correlations change over time• Our CSWM Market Stress Indicator has been constructed around the notion that stress,

like portfolio volatility, is a function of both volatility and correlation

• Looking at equity/bond correlations in this way reveals a “Normal” positive correlation…

Equity/Bond correlations and VIX Equity/Commodity correlations and VIX

-60%

-40%

-20%

0%

20%

40%

60%

-10 0 10 20 30 40 50 60 70

VIX

Aver

age

equi

ty b

ond

corre

latio

ns

-20%

-10%

0%

10%

20%

30%

40%

50%

-10 0 10 20 30 40 50 60 70

VIX

Aver

age

equi

ty c

omm

odity

cor

rela

tions

Three main problems with MPT

•Non constant moments - volatility and correlation across asset classes change over time

•Resulting portfolio may not be well diversified

•Small changes to inputs can lead to large changes to the output

Problem #1: Non constant moments - CSWM Market Stress Indicator

• Our CSWM Market Stress Indicator has been constructed around the notion that stress, like portfolio volatility, is a function of both volatility and correlation

CSWM Market Stress Indicator v S&P (total return)

200

250

300

350

400

450

500

550

600

650

700

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

200

250

300

350

400

450

500

550

600

650

700Normal

Stressed

S&P

CSWM Market Stress Indicator - Stability• Since 1991, the indicator has been stressed c.20% of the time (daily data)

• It’s stability is paramount – many false signals could be costly

• Statistically, you are more likely to be in the same state that you are in today, in one month’s time

• The probability of moving through two states in one month is small

Equity/Bond correlations and VIX CSWM Market Stress Indicator – Markov matrix

0%

5%

10%

15%

20%

25%

30%

35%

40%

1 2 3 4 5

0%

5%

10%

15%

20%

25%

30%

35%

40%

StressNormal

Probability of stress state in 1 month

1 2 3 4 5

1 73% 19% 6% 2% 0%

2 2% 52% 39% 7% 0%

3 17% 29% 28% 25% 0%

4 2% 11% 27% 45% 15%

5 0% 0% 8% 53% 39%Stre

ss s

tate

now

• Our approach is to manage both absolute and relative risk simultaneously

Problem #2: Optimised portfolios lack diversification