Majlis Factbook Prentation by Creativei Corp

MAJLIS PARTNERS

Factbook – The Industry Problem April 2011

Table of Contents

Stock & Bonds Selection

Slides 3 - 25

II.

Time Pickers

Slides 26 - 28

III. Manager Selection

Slides 29 – 37

IV. Style Drift

Slides 38 - 40

Slide 41

Silent Partners

VI. Financial Theory

Slides 42 - 46

VII. Footnotes

Slides 47 - 49

Private & Confidential

I. Stock & Bonds Selection Stock pickers are active investors who bet they can beat a market by picking stocks they believe will outperform an index or market average. •

The main reason that stock pickers fail is that stock prices are moved by news, and news tends to be unpredictable and random in nature. Therefore, the movement of stock prices tends to be unpredictable and random.

Why Stock Pickers Fail

•

―Survivorship bias‖ is one of the many reasons that stock pickers’ returns look better than they actually are. Survivorship bias is when mutual fund managers tout their fund’s performance based on comparisons with an ―average‖ mutual fund. This average is calculated from a list of funds that have survived during a particular period. Funds that did not survive the period are not included in the calculation.

Revolving Door

•

Finally, there are the revolving doors of stockbrokers who are churning through clients and constantly rotating from one firm to another. Their records are quickly extinguished, never to be counted in the average of stock pickers.

Stock Pickers are Focused on Short Term

•

The confusion of most investors is derived from their inability to look at large sets of data about stocks, times, managers or styles. This is similar to saying that an investor feels confident about a certain stock, time period, manager or style based on a recent short-term experience.

• Figure 1-2 shows that Investors, who think they see a pattern in monthly or quarterly returns are experiencing random drift, just like 50 rolls of the dice. They are being fooled by randomness.

• Figure 1-1 shows that in the 41 years from 1957 to 1998, only 74 of the original 500 companies were still in existence and only 12 of those outperformed the S&P 500 Index over the 1957 to 1998 period.

Figure 1-2

Figure 1-1

Private & Confidential

Stock Pickers are Looking for a Needle in a Haystack

Stock Pickers Play a Zero Sum Game

•

John Bogle accurately described stock picking as looking for a needle in a haystack. The top 10 stocks perform 20 times better in their first three years than they do in the following three years, according to a study by Ibbotson and Associates.

•

Stock pickers are often surprised when they purchase what they think have been winners, only to be grossly disappointed in the period after purchase.

•

All financial markets are zero sum games. This is a mathematical fact. In any financial market it is mathematically impossible for the average investor in that market to outperform the average of the market.

•

This is because in any market, the pre-cost returns earned by good, bad, and average stock pickers combined together must be the same as the total market return.

•

The after-cost returns will be less than the total market return. All investors as a group are mathematically obligated to underperform the market by the amount of their costs of investing.

Stories From Blue Chips Companies From 1959 to 2010

• Many investors invest in blue chip companies, believing they are reliable and true blue. See Figure 1-3 for less than favorable outcomes of 10 of these blue chip companies.

Figure 1-3

Private & Confidential

Stock Pickers in International Markets

Stock Pickers don’t Want You to Know the Truth

•

Several studies have proven that the indexes of these smaller markets, on average, will perform better than an active fund.

•

In fact, there have been studies that show higher costs associated with international investing make it even harder for active investors to beat their benchmarks.

•

This is because stock pickers and analysts charge very high fees on mutual funds, and these fees pay for a lot of the jobs in the industry. It is in the interest of these stock, time, manager, and style pickers to imply that a market can be beat by listening to their strategist or by risking money with their manager.

Size Risk Factor for U.S. Equities 83 Years (1/1/1928 – 12/31/2010)

• The average return of small-cap company stocks have significantly outperformed large company stocks over the last 80 years by 3.13% per year. But, to get higher returns, investors must accept a step up in the uncertainty of those returns. Figure 1-4 plots the deciles (one-tenth buckets) of U.S. companies sorted by size over the last 81 years. Note that a fairly clear line exists between the less risky large-cap stocks in decile 1 and the very risky microcap stocks in decile 10.

Figure 1-4

Private & Confidential

Stock Pickers Dilute the Two Most Important Risk Factors

•

An active manager investing in a portfolio of value and small company stocks with favorable prospects holds a portfolio biased towards growth and large company stocks. But it’s not growth and large company stocks that have the highest expected returns. It’s value and small company stocks — companies with the highest costs of capital.

Value, Blend and Growth Indexes Around the World Annualized Returns and Standard Deviation Over Various Periods

• Long-term investment data makes it clear that value stocks outperform growth stocks and small company stocks outperform large company stocks, as seen in the 80 years of returns data from all over the world seen in Figure 1-7.

Figure 1-7

Private & Confidential

The Majlis Matrix • Passive Beats Active in Equities and Fixed Income ( Various Time Periods 1970 - 2009)

Equities Percentage underperforming 345 Funds vs. S&P 500 1970 - 2000 (31 Years)1

Percentage overperforming 355 Funds vs. S&P 500 1970 - 1999 (30 Years)2

Large-Cap Equity Funds vs. the S&P 500 Index 1996 - 2005 (10 Years)4

3,0%

2,5%

5,5%

71 Large Cap Growth/Growth & Income Mutual Fund Managers vs. the S&P 500 I. 2001 - 2006 (5 Y.)3

18,0%

21,0%

94,5%

82,0%

79,0%

97,0%

97,5%

Large-Cap Equity Funds vs. the S&P 500 Index 1986 - 2005 (20 Years)5

Fixed Income 125 High Yield Funds vs. BarCap

570 Peer Bond Funds vs. Vanguard

Intermediate Bond Fund High Yield 2005 - 2009 overperforming percentage underperforming Percentage 1996 - 2006 (10 Years)2 ( 5 Years)1 79% 21%

3,3%

4,8%

194 Peer Bond Funds vs. Vanguard Long-Term Muni Bond Fund 1996 - 2006 (10 Years) 3

47 Government Long Fund vs. BarCap Long Government Fund 2005 - 2009 (5 Years)4

0,0% 27,7%

95,2 % 42 Government Short Fund vs. BarCap 1-3 Years Government Index 2005 -2009 (5 Years)6

100,0 %

73,8%

29,4%

70,6%

72,3%

96,7% 103 Investment-Grade Long Funds vs. BarCap Long Gov't/Credit I. 2005 - 2009 (5 Y) 7

63 Investment-Grade Short Funds vs. BarCap 1-3 Years Gov't/Credit Index 2003 - 2008 (5 Years)9

81 General Municipal Debt Funds vs. S&P National AMT-Free Municipal Bond I. 2005 - 2009 (5 Y) 10

3,2%

25,2%

26,2%

51 Government Intermediate Funds vs. BarCap Intermediate Government I. 2005 - 2009 (5 Y.)5

74,8%

11,1%

2,0%

88,9%

96,8%

819 Mutual Fund Managers vs. Benchmark 1962 - 2006 (45 Years)12

98,0%

Source: Standard & Poors Figure 1-8

Private & Confidential

Excellent vs. Unexcellent Company Fundamentals

Excellent vs. Unexcellent Company

US Companies

Portfolio Returns - US Companies 1981 -1985

12.92% 10.74%

10.65%

280

9.37%

297.5%

260

6.40% 4.77%

Unexcellent Companies

300

3.91% 240 2.11%

Asset Growth

Equity Growth

0.98%

Market/ Book Ratio

1.68%

Return on Total Capital

1.35%

220

Return on Sales

200

Excellent Companies

180 160 140

Excellent Companies

181.6%

120 -15.08%

Return on Equity

Unexcellent Companies

100 80 Jan 81

Michelle Clayman, ―In Search of Excellence: The Investor’s Viewpoint,‖ Financial Analysts Journal 43, no. 3 (May/June 1987): 54-63.

• Economic health is (often) easily observed.

Private & Confidential

Dec 82

Dec 83

Dec 84

Dec 85

Michelle Clayman, ―In Search of Excellence: The Investor’s Viewpoint,‖ Financial Analysts Journal 43, no. 3 (May/June 1987): 54-63. Figure 1-10

Figure 1-9

Dec 81

• For a given level of future earnings, a lower price paid means a higher expected investment return.

The Majlis Matrix of Developed Countries 1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

USA 38 % SWE 34 % HKG 23 % NLD 22 % GBR 21 % CAN 19 % DEU 17 % FR A 15 % AUS 12 % JPN 1%

SWE 38 % HKG 33 % CAN 29 % GBR 27 % USA 24 % FR A 22 % NLD 19 % AUS 18 % DEU 14 % JPN -15 %

USA 34 % DEU 25 % GBR 23 % CAN 13 % SWE 13 % FR A 12 % AUS -10 % NLD -13 % HKG -23 % JPN -24 %

FR A 42 % USA 31 % DEU 30 % GBR 18 % SWE 15 % AUS 7% JPN 5% HKG -3 % CAN -6 % NLD -21 %

SWE 81 % JPN 62 % HKG 60 % CAN 54 % FR A 30 % USA 22 % DEU 21 % AUS 19 % NLD 14 % GBR 12 %

CAN 6% FR A -4 % AUS -9 % GBR -12 % USA -13 % DEU -15 % HKG -15 % SWE -21 % JPN -28 % NLD -33 %

NLD 10 % AUS 3% USA -12 % GBR -14 % HKG -19 % CAN -20 % FR A -22 % DEU -22 % SWE -27 % JPN -29 %

NLD 26 % AUS 0% JPN -10 % CAN -13 % GBR -15 % HKG -18 % FR A -21 % USA -23 % SWE -30 % DEU -33 %

SWE 66 % DEU 65 % NLD 58 % CAN 55 % AUS 51 % FR A 41 % HKG 38 % JPN 36 % GBR 32 % USA 29 %

NLD 38 % SWE 37 % AUS 32 % HKG 25 % CAN 23 % GBR 20 % FR A 19 % DEU 17 % JPN 16 % USA 11 %

CAN 29 % JPN 26 % AUS 18 % FR A 11 % DEU 11 % SWE 11 % HKG 8% GBR 7% USA 6% NLD 3%

SWE 45 % DEU 37 % FR A 35 % AUS 33 % GBR 31 % HKG 30 % CAN 18 % NLD 18 % USA 15 % JPN 6%

HKG 41 % DEU 36 % AUS 30 % CAN 30 % FR A 14 % NLD 10 % GBR 8% USA 6% SWE 1% JPN -4 %

JPN -29 % USA -37 % FR A -43 % CAN -45 % DEU -45 % GBR -48 % SWE -49 % AUS -50 % HKG -51 % NLD -53 %

AUS 77 % SWE 66 % HKG 60 % CAN 57 % NLD 52 % GBR 43 % FR A 33 % DEU 27 % USA 27 % JPN 6%

So urce: M scibarra

AUS

CAN

A ustralia

Canada

FRA

France

HKG

Ho ng Ko ng

DEU

Germany

JPN

Japan

NLD

SWE

New Zealand

GBR

United Kingdo m

Sweden

USA

Figure 1-11

Private & Confidential

The Majlis Matrix of Industrial Sectors 1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

H 16 % CS 5% T 0% U -1 % E -2 % M -7 % CD -22 % R -29 % F -33 %

H 62 % R 57 % F 48 % CS 45 % M 30% T 29 % U 24 % CD 18 % E 7%

F 57 % CD 38 % R 36 % M 10 % T 10 % U 8% CS 5% E 5% H -15 %

CD 44 % F 33 % T 21 % M 17 % CS 14 % E 14 % U 13 % R 12 % H -7 %

T 18 % H 7% M 6% E 3% CS 2% F 2% U -11 % CD -15 % R -20 %

H 57 % F 44 % T 43 % CS 36 % U 32 % M 31 % E 28 % CD 15 % R 1%

T 31 % E 27 % M 26 % F 24 % CS 23 % H 17 % CD 15 % R 14 % U 7%

F 52 % H 38 % CS 32 % U 28 % CD 28 % M 24 % T 22 % E 20 % R 15 %

T 63 % H 38 % CD 30 % R 20 % U 11 % CS 10 % M 6% E -2 % F -5 %

T 81 % M 24 % E 20 % R 3% F 2% H -3 % CD -4 % U -14 % CS -15 %

U 52 % H 38 % CS 23 % E 22 % F 8% M 1% CD -17 % R -28 % T -38 %

R 50 % F 32 % CD 7% CS 0% M -7 % E -7 % U -11 % H -12 % T -25 %

F 12 % CS -2 % R -6 % M -7 % E -9 % CD -15 % U -23 % H -23 % T -38 %

F 57 % R 56 % CD 49 % T 48 % M 33 % U 26 % E 26 % H 22 % CS 20 %

E 33 % U 25 % R 25 % F 20 % M 16 % CS 10 % CD 9% T 5% H 0%

E 34 % U 17 % R 10 % M 7% H 5% F 5% CS 2% T 1% CD -20 %

CD 22 % U 21 % E 21 % M 19 % CS 18 % R 17 % F 17 % T 9% H 8%

E 32 % M 21 % U 19 % T 16 % CS 12 % H 4% CD -3 % F -19 % R -21 %

H -17 % CS -24 % U -29 % E -34 % F -38 % M -41 % T -42 % R -49 % CD -59 %

R 111 % CD 80 % T 58 % M 35 % CS 26 % H 21 % U 15 % E 15 % F 6%

So urce: M scibarra

Co nsumer Discretio nary

Energy

Healthcare

Co nsumer Staples

Financials

Retail

M anufacturing

Utilities

Techno lo gy

Figure 1-12

ÂŠ 2011 Majlis Partners

Private & Confidential

The Majlis Matrix of Benchmark Returns • Annual Returns for Key Indices (2000-2010) Ranked in Order of Performance 2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

B arclays 10 Year US Treasury 15.34 %

B arclays 1-3 Year US Treasury 8.23 %

P SE Go ld and Silver 41.02 %

M SCI Emerging M arkets 51.59 %

M SCI Emerging M arkets 22.45 %

Nikkei 225 40.23 %

M SCI Emerging M arkets 29.18 %

M SCI Emerging M arkets 36.48 %

B arclays 10 Year US Treasury 18.94 %

M SCI Emerging M arkets 74.5 %

P SE Go ld and Silver 34.68 %

B arclays 1-3 Year US Treasury 7.73 %

B arclays 10 Year US Treasury 6.52 %

B arclays 10 Year US Treasury 15.15 %

P SE Go ld and Silver 41.8 %

M SCI EA FE 17.59 %

M SCI Emerging M arkets 30.31%

M SCI EA FE 23.47 %

P SE Go ld and Silver 21.86 %

B arclays 1-3 Year US Treasury 6.38 %

P SE Go ld and Silver 36.67 %

M SCI Emerging M arkets 16.4 %

S&P 500 -10.14 %

P SE Go ld and Silver 5.88 %

B arclays 1-3 Year US Treasury 5.53 %

M SCI A C A SIA 36.83 %

M SCI A C A SIA 14.58 %

P SE Go ld and Silver 28.88 %

M SCI Wo rld 17.95 %

B arclays 10 Year US Treasury 10.45 %

P SE Go ld and Silver -28.54 %

M SCI Wo rld 25.97 %

M SCI A C A SIA 15.2 %

FTSE 100 -10.21%

M SCI Emerging M arkets -4.91%

M SCI Emerging M arkets -7.97 %

M SCI EA FE 35.28 %

M SCI Wo rld 12.84 %

M SCI A C A SIA 22.48 %

S&P 500 13.62 %

M SCI A C A SIA 10.31%

FTSE 100 -31.32 %

M SCI EA FE 25.45 %

S&P 500 12.79 %

M SCI Wo rld -14.05 %

S&P 500 -13.04 %

M SCI A C A SIA -10.88 %

M SCI Wo rld 30.81%

S&P 500 8.99 %

FTSE 100 16.72 %

M SCI A C A SIA 12.77 %

M SCI EA FE 8.62 %

S&P 500 -38.5 %

M SCI A C A SIA 25.25 %

M SCI Wo rld 9.55 %

M SCI EA FE -15.21%

FTSE 100 -16.15 %

Nikkei 225 -16.35 %

S&P 500 26.38 %

Nikkei 225 7.62 %

M SCI EA FE 10.86 %

P SE Go ld and Silver 11.09 %

B arclays 1-3 Year US Treasury 7.3 %

M SCI A C A SIA -41.62 %

S&P 500 24.12 %

B arclays 10 Year US Treasury 9.43 %

P SE Go ld and Silver -24.37 %

M SCI Wo rld -17.83 %

M SCI EA FE -17.52 %

Nikkei 225 24.45 %

FTSE 100 7.54 %

M SCI Wo rld 7.56 %

FTSE 100 10.72 %

M SCI Wo rld 7.09 %

M SCI Wo rld -42.08 %

FTSE 100 22.07 %

FTSE 100 9.01%

Nikkei 225 -27.19 %

M SCI EA FE -22.61%

M SCI Wo rld -21.06 %

FTSE 100 13.59 %

B arclays 10 Year US Treasury 4.64 %

S&P 500 3 %

Nikkei 225 7.68 %

FTSE 100 3.8 %

Nikkei 225 -42.13 %

Nikkei 225 19.04 %

M SCI EA FE 4.9 %

M SCI A C A SIA -30.37 %

Nikkei 225 -23.53 %

S&P 500 -23.37 %

B arclays 10 Year US Treasury 1.97 %

B arclays 1-3 Year US Treasury 0.84 %

B arclays 10 Year US Treasury 2.87 %

B arclays 1-3 Year US Treasury 3.92 %

S&P 500 3.54 %

M SCI EA FE -45.09 %

B arclays 1-3 Year US Treasury 0.85 %

B arclays 1-3 Year US Treasury 2.58 %

M SCI Emerging M arkets -31.8 %

M SCI A C A SIA -23.82 %

FTSE 100 -24.48 %

B arclays 1-3 Year US Treasury 1.93 %

P SE Go ld and Silver -8.71%

B arclays 1-3 Year US Treasury 1.62 %

B arclays 10 Year US Treasury 2.23 %

Nikkei 225 -10.82 %

M SCI Emerging M arkets -54.48 %

B arclays 10 Year US Treasury -6.81%

Nikkei 225 -3 %

Source: Majlis Partners Figure 1-13

Private & Confidential

The Majlis Matrix of Hedge Fund Benchmark Returns • Annual Returns for Key Indices (2000-2010) Ranked in Order of Performance 2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

Barclay M ult iSt rat egy HF 2 1. 6 6 %

Eurekahedge EM HF Index 2 0 . 78 %

DJCS M anaged Fut ures HF 18 . 3 4 %

Eurekahedge EM HF Index 3 9 .0 9 %

Barclay Dist ressed Securit ies HF 18 . 4 5 %

Eurekahedge LongOnly Abs. Ret . Fund 2 2 . 15 %

Eurekahedge EM HF Index 2 6 .3 %

Eurekahedge EM HF Index 2 5. 13 %

DJCS M anaged Fut ures HF 18 . 3 3 %

Barclay Convert ible Arbit rage HF 53 . 6 2 %

Eurekahedge LongOnly Abs. Ret . Fund 15. 0 2 %

Barclay M erger Arbit rage HF 19 . 2 6 % Eurekahedge Hedge Fund Index 17. 56 %

DJCS Global M acro HF 18 . 3 8 % Barclay Dist ressed Securit ies HF 17. 0 6 %

Eurekahedge EM HF Index 16 . 8 8 % DJCS Global M acro HF 14 . 6 7 %

Eurekahedge LongOnly Abs. Ret . Fund 3 6 .2 5 % Barclay Dist ressed Securit ies HF 2 5. 58 %

Eurekahedge EM HF Index 17. 3 6 % Eurekahedge LongOnly Abs. Ret . Fund 16 . 6 4 %

Eurekahedge EM HF Eurekahedge Long- Eurekahedge Islamic Index Only Abs. Ret . Fund Fund Index 18 . 9 6 % 19 . 9 8 % 19 . 58 % Eurekahedge Hedge Barclay Event Driven DJCS Global M acro Fund Index HF HF 11. 2 5 % 15. 59 % 17. 3 7 %

Barclay M erger Arbit rage HF - 3 .3 8 % DJCS Global M acro HF - 4 .6 2 %

Eurekahedge LongOnly Abs. Ret . Fund 4 7. 4 8 % Eurekahedge EM HF Index 3 5. 8 7 %

Barclay Dist ressed Securit ies HF 14 . 0 2 % DJCS Global M acro HF 13 . 4 5 %

Barclay Convert ible Arbit rage HF 15. 3 1 %

Barclay Convert ible Barclay Convert ible Barclay Event Driven Barclay Event Driven Barclay Hedge Fund Arbit rage HF Arbit rage HF HF HF 10 . 6 8 % 16 . 58 % 10 . 6 4 % 2 2 .0 4 % 16 . 13 % Eurekahedge Hedge Eurekahedge Hedge Eurekahedge Hedge DJCS Long/ Short Eurekahedge Islamic Fund Index Fund Index Fund Index Equit y HF Fund Index 11. 0 5 % 7. 3 3 % 2 0 .9 9 % 11. 57 % 9 . 78 % Barclay M ult iBarclay Fixed Eurekahedge Hedge DJCS Long/ Short Barclay Hedge Fund St rat egy HF Income Arbit rage HF Fund Index Equit y HF 17. 9 8 % 10 . 53 % 7. 0 9 % 9 .9 9 % 9 .6 8 %

Barclay Hedge Fund 12 . 19 % Barclay Event Driven HF 12 . 0 8 %

Barclay Fixed Barclay Event Driven Income Arbit rage HF HF 11. 75 % 8 .3 4 % DJCS Global M acro Eurekahedge LongHF Only Abs. Ret . Fund 11. 6 9 % 7. 2 7 %

Barclay Dist ressed Securit ies HF 6 .3 8 % Barclay M ult iSt rat egy HF 6 .2 8 %

DJCS Global M acro HF 17. 9 7 % DJCS Long/ Short Equit y HF 17. 3 %

Barclay Fund of Barclay Hedge Fund Funds HF 6 . 77 % 10 . 2 1 % Eurekahedge Fund Barclay Fixed of Funds Index Income Arbit rage HF 10 . 13 % 6 .0 6 % Eurekahedge EM HF Eurekahedge Fund Index of Funds Index 7. 3 6 % 5. 9 4 %

Eurekahedge Fund of Funds Index 2 .3 7 % Barclay Fund of Funds HF 1. 8 1 %

Barclay Dist ressed Securit ies HF 5. 3 5 % DJCS M anaged Fut ures HF 4 .2 5 %

Barclay Fund of Funds HF 4 .4 6 % Barclay M erger Arbit rage HF 3 . 12 %

DJCS Long/ Short Equit y HF 2 .0 8 %

DJCS M anaged Fut ures HF 1. 9 2 %

Eurekahedge LongOnly Abs. Ret . Fund - 1. 3 8 % Eurekahedge Islamic Fund Index - 7. 8 7 %

DJCS Long/ Short Equit y HF - 3 .6 7 % Eurekahedge Islamic Fund Index -4 %

Barclay Hedge Fund 1. 4 % Barclay M erger Arbit rage HF - 0 . 11 % DJCS Long/ Short Equit y HF - 1. 6 %

Eurekahedge Long- Eurekahedge Hedge Barclay Dist ressed DJCS M anaged Only Abs. Ret . Fund Fund Index Securit ies HF Fut ures HF 16.98 % - 10 . 8 1 % 3 0 .9 2 % 12 . 2 % Barclay M erger Barclay Event Driven Barclay Event Driven Barclay Convert ible Arbit rage HF HF HF Arbit rage HF 13 . 9 6 % - 17. 4 7 % 2 9 . 11 % 12 . 16 % Eurekahedge Hedge Barclay M ult iBarclay M ult iBarclay Fixed Fund Index St rat egy HF St rat egy HF Income Arbit rage HF 13 . 9 5 % - 17. 9 7 % 2 5. 8 1 % 11. 6 6 %

DJCS Global M acro HF 9 .2 5 % DJCS Global M acro Barclay Event Driven HF HF 8 .4 9 % 8 .2 1 %

Barclay M ult iSt rat egy HF 13 . 8 7 % Eurekahedge Hedge Fund Index 13 . 8 %

DJCS Long/ Short Equit y HF 13 . 6 5 % Eurekahedge Fund of Funds Index 10 . 4 1 %

Eurekahedge Fund of Funds Index - 19 . 3 3 % DJCS Long/ Short Equit y HF - 19 . 74

Eurekahedge Islamic Fund Index 17. 1 % DJCS M anaged Fut ures HF 14 . 15 % Barclay M ult iSt rat egy HF 11. 6 9 %

Eurekahedge Islamic Fund Index 8 .2 % Barclay Fixed Income Arbit rage HF 7. 13 % Eurekahedge Fund of Funds Index 6 .9 5 %

Eurekahedge Fund of Funds Index 8 .0 3 % Barclay Dist ressed Securit ies HF 7. 8 6 % Barclay Fund of Funds HF 6 .9 %

DJCS Global M acro HF 13 . 54 %

Barclay Hedge Fund 10 . 2 3 %

Barclay Hedge Fund - 2 1. 6 3 %

Eurekahedge Fund of Funds Index 11. 52 % Barclay Fund of Funds HF 10 . 4 4 %

Barclay Fund of Funds HF 6 .6 7 % Barclay M ult iSt rat egy HF 6 .3 1 %

Barclay M ult iSt rat egy HF 6 .4 5 % Barclay M erger Arbit rage HF 5. 4 %

Eurekahedge Fund of Funds Index 10 . 4 5 % Barclay Fund of Funds HF 9 .3 8 %

DJCS M anaged Fut ures HF 5. 9 6 %

Barclay Fixed Income Arbit rage HF 4 . 72 %

DJCS M anaged Fut ures HF 8 .0 5 %

Barclay Event Driven Barclay Fixed HF Income Arbit rage HF - 2 .8 5 % 10 . 0 4 % Eurekahedge LongOnly Abs. Ret . Fund - 4 .0 5 % Eurekahedge Islamic Fund Index - 7. 4 2 %

Barclay Dist ressed Securit ies HF 14 . 6 9 % DJCS Long/ Short Equit y HF 14 . 3 8 % Barclay M erger Arbit rage HF 14 . 0 5 %

Barclay Convert ible Arbit rage HF 9 .8 % Barclay M erger Arbit rage HF 8 .4 4 %

Barclay Hedge Fund 8 . 79 %

Barclay M erger Arbit rage HF 5. 2 1 % Barclay Convert ible Arbit rage HF 0 .9 9 %

Barclay Hedge Fund 12 . 3 9 % Barclay Convert ible Arbit rage HF 11. 73 %

Barclay M ult iSt rat egy HF 9 . 56 % Barclay Fund of Funds HF 8 .8 6 %

DJCS M anaged Barclay Fixed Barclay Convert ible Fut ures HF Income Arbit rage HF Arbit rage HF - 0 . 11 % 6 .0 5 % 2 .6 5 % Barclay Convert ible Eurekahedge Islamic Barclay Fixed Arbit rage HF Fund Index Income Arbit rage HF - 3 .2 1 % 4 . 11 % - 0 .6 1 %

Barclay Hedge Fund 10 . 8 8 %

Eurekahedge Islamic Fund Index 2 1. 6 6 %

Eurekahedge Hedge Fund Index 10 . 8 %

Eurekahedge Hedge Barclay M ult iFund Index St rat egy HF 2 0 .0 2 % 10 . 78 % Barclay Fund of Barclay Fixed Eurekahedge EM HF Funds HF Income Arbit rage HF Index - 2 2 . 19 % 19 . 8 3 % 10 . 76 % Eurekahedge EM HF DJCS Long/ Short Barclay Event Driven Index Equit y HF HF - 2 3 .6 7 % 19 . 4 6 % 9 .9 8 %

Barclay Event Driven Barclay Fixed HF Income Arbit rage HF 8 .3 7 % - 2 5. 2 % Barclay Dist ressed Barclay Convert ible Securit ies HF Arbit rage HF 6 .9 2 % - 2 7. 6 6 % DJCS M anaged Fut ures HF 6 %

Barclay Hedge Fund 2 3 . 73 %

Barclay M erger Arbit rage HF 11. 72 % DJCS Global M acro HF 11. 54 %

Eurekahedge Islamic Fund Index 9 . 58 % DJCS Long/ Short Equit y HF 9 .2 7 %

Eurekahedge Islamic Fund Index - 2 8 . 58 %

Barclay Fund of Funds HF 10 . 2 4 %

Barclay M erger Arbit rage HF 6 .0 6 %

Barclay Dist ressed Securit ies HF - 3 1. 7 % Eurekahedge LongOnly Abs. Ret . Fund - 4 1. 9 4 %

Eurekahedge Fund of Funds Index 9 .5 % DJCS M anaged Fut ures HF - 6 . 58 %

Barclay Fund of Funds HF 4 .8 9 % Eurekahedge Fund of Funds Index 4 .4 4 %

Source: Majlis Partners Figure 1-14

Private & Confidential

• Asset class returns vary considerably from year to year, and past returns offer little insight into future performance. However, combining multiple asset classes tends to minimise the volatility associated with this random behaviour. Global diversification reduces the effect of a single asset class or market. • The historical returns chart offers compelling evidence that structured portfolios are a reliable way to capture the returns associated with multiple measures of risk across the global capital markets. • The upper chart ranks the year-to-year returns (from highest to lowest) of the model portfolios using the corresponding colours. • The lower chart features historical annual performance of the model portfolios for each of the last seventeen years, with the far right columns showing annualised returns and standard deviations for the entire period.

Balanced Strategies: Historical Returns In GBP Equity

Highest Return

Lowest Return

80/20

60/40

40/60

Fixed

20/80

1996

1997

1998

1999

2000

2003

2004

2005

2006

2007

2008

2009

2010

8.23

15.00

7.12

33.47

5.74

32.05

15.79

27.31

15.07

5.44

4.59

32.60

20.12

7.80

13.42

7.09

27.42

4.52

26.00

13.44

22.54

12.98

5.10

-3.88

26.02

16.11

7.34

11.77

6.87

21.56

3.26

20.11

11.12

17.88

10.88

4.66 -11.59

19.48

12.11

6.84

10.07

6.45

15.87

1.97

14.38

8.82

13.33

8.78

4.19 -18.95

12.99

8.13

6.32

8.32

5.82

10.37

0.63

8.81

6.53

8.89

6.68

3.68 -25.95

6.59

4.17

5.77

6.52

4.99

5.04

-0.75

3.41

4.32

4.47

4.49

3.14 -32.60

0.31

0.22

Annual Annualised Standard Return Deviation

Equity

1996 8.23

1997 15.00

1998 4.99

1999 33.47

2000 2001 2002 -0.75 -7.45 -23.71

2003 32.05

2004 15.79

2005 27.31

2006 15.07

2007 2008 3.14 -32.60

2009 32.60

2010 20.12

7.67

19.78

80/20

7.80

13.42

5.82

27.42

0.63

-4.79 -18.51

26.00

13.44

22.54

12.98

3.68

-25.95

26.02

16.11

7.26

15.77

60/40

7.34

11.77

6.45

21.56

1.97

-2.24 -13.16

20.11

11.12

17.88

10.88

4.19

-18.95

19.48

12.11

6.72

11.76

40/60

6.84

10.07

6.87

15.87

3.26

0.22

-7.66

14.38

8.82

13.33

8.78

4.66

-11.59

12.99

8.13

6.05

7.77

20/80

6.32

8.32

7.09

10.37

4.52

2.56

-2.05

8.81

6.53

8.89

6.68

5.10

-3.88

6.59

4.17

5.26

3.94

Fixed

5.77

6.52

7.12

5.04

5.74

4.78

3.69

3.41

4.32

4.47

4.49

5.44

4.59

0.31

0.22

4.38

1.94

Standard deviation is a statistical measure of risk where past performance is used to determine the range of possible future performance. Generally speaking, the higher the standard deviation, the greater the risk. Assumes all strategies have been rebalanced monthly. All balanced strategies information is based on returns of indexes with model/back-tested allocations. The returns were achieved with the benefit of hindsight and do not represent actual investment strategies. The model’s returns reflect hypothetical fund manager fees. There are limitations inherent in model allocations. In particular, model returns may not reflect the impact that economic and market factors may have had on the adviser’s decision making if the adviser were managing actual client money. This material has been distributed by Dimensional Fund Advisors Ltd., which is authorised and regulated by the Financial Services Authority. Past performance is no guarantee of future results. Figure 1-15

Private & Confidential

• The dispersion of colours now appears mostly uniform and consistent, with the more diversified model portfolios prevailing in the majority of one-year time periods. This example illustrates how markets tend to reward investors for the risks they bear, with riskier strategies generally offering higher expected returns.

Non-Surviving Equity Funds Actively Managed US Equity Funds 2005-2009 • On average, 7.0% of the actively managed equity fund universe disappeared each year. • During 2005, 6.8% of the fund universe disappeared. By the fifth year, 30.4% of the fund universe (677 funds) had disappeared. • Reasons for non-survival likely include closure due to poor investment results. • Some people claim that strong financial markets offer opportunities for active managers to add value, while others say that active management works best in market downturns. During the past five years, the US stock market has experienced several years of moderate gains and one year of extreme underperformance (2008). • As shown in this graph, of the 2,231 actively managed US equity funds operating at the beginning of 2005, 30% of the universe disappeared during the five-year period through 2009. Most of this non-survival occurred in years when the market delivered positive returns. Data provided by CRSP Survivor-Bias-Free US Mutual Fund Database. Sample includes mutual funds existing as of 12/2004. Returns analyzed for the five-year period from 2005-2009. Multiple share classes are aggregated to fund level. Index funds, inverse funds, and leveraged funds are excluded. Figure 1-16

Private & Confidential

• Some investors might conclude that a 70% survival rate offered strong odds of choosing a successful fund over the period, with a fund’s success defined as beating the performance benchmark for its fund category. But survival rate alone does not offer insight into future performance of a fund, as demonstrated in the next slide.

Size and Value Effects Are Strong around the World

Annualised Compound Returns (%)

• The size and BtM effects appear in both UK and international markets—strong evidence that the risk factors are systematic across the globe. • Higher expected returns are offered by small cap stocks and value (high BtM) stocks in the UK, Europe ex UK, US, and emerging markets. Note that the international and emerging markets data is for a shorter time frame. • Small cap stocks are considered riskier than large cap stocks, and value stocks (as defined by a higher book-to-market ratio) are deemed riskier than growth stocks. These higher returns reflect compensation for bearing higher risk. • A multifactor approach incorporates both size and value measures—and exposure to non-UK markets—in an effort to increase expected returns and reduce portfolio volatility. An effective way to capture these effects is through portfolio structure.

UK Large Value

FTSE AllShare

UK Large Growth

UK Large Capitalisation Stocks (£) 1956–2010 Standard 31.78 28.33 Deviation (%)

26.05

UK UK Small Small Value Market

UK Small Growth

UK Small Capitalisation Stocks (£) 1956–2010 31.52

30.11 30.69

Europe MSCI Europe Large Europe Large Value Index Growth

Europe Large Capitalisation Stocks (€) 1981–2010 24.51

21.76

22.14

Europe Europe Europe Small Small Small Value Market Growth

Europe Small Capitalisation Stocks (€) 1981–2010 24.91

23.22

26.79

US Large Value

S&P 500 Index

US Large Growth

US Large Capitalisation Stocks ($) 1927–2010 27.01

20.51 21.93

US Small Value

CRSP US 6-10 Small Index Growth

US Small Capitalisation Stocks ($) 1927–2010 35.13

30.94 34.05

Emg. Emg. Emg. Markets Markets Markets Value ―Market‖ Growth

Emerging Markets Capitalisation Stocks ($) 1989–2010 42.01

36.40

Value stocks are above the 30th percentile in book-to-market ratio. Growth stocks are below the 70th percentile in book-to-market ratio. Simulations are free-float weighted both within each country and across all countries. UK and Europe data provided by London Business School/StyleResearch. US value and growth index data (ex utilities) provided by Fama/French. FTSE data published with the permission of FTSE. The S&P data are provided by Standard & Poor’s Index Services Group. CRSP data provided by the Center for Research in Security Prices, University of Chicago. MSCI Europe Index is gross of foreign withholding taxes on dividends; copyright MSCI 2011, all rights reserved. Emerging Markets index data simulated by Fama/French from countries in the IFC Investable Universe. Figure 1-18

Private & Confidential

34.89

Distribution of US Market Returns CRSP 1-10 Index Returns by Year (1926–2010) • In 2008, the US stock market experienced its second worst performance year since 1926. • In 2009, US market performance was in the top quartile of historical calendar year returns. • While no one can reliably predict the future, the past may offer perspective on recent market events and the long-term benefits of equity investing. • Performance over the past two years has been extreme by historical standards, and that, over time, the market’s positive return years have outnumbered the negative return years, with positive performance more concentrated in the higher ranges of returns. • History shows that the stock market has rewarded investors who can bear the risk of stocks and stay committed through various periods of performance.

1949 20.2

Positive Years: Negative Years:

1951 20.7

63 (74%) 22 (26%)

1963 21.0 1982 21.0

1970 0.0

1944 21.3

1953 0.7

1993 11.1

1996 21.4

1960 1.2

2004 12.0

1983 22.0

1987 1.7

1959 12.7

1979 22.6

1948 2.1

1952 13.4

1998 24.3

1997 31.4

1939 2.9

1968 14.1

1955 25.2

2003 31.6

1947 3.6

1965 14.5

1999 25.3

1985 32.2

1973 -18.1

1966 -8.7

1934 4.3

2006 15.5

1976 26.8

1936 32.3

1929 -14.6

1932 -8.7

1984 4.5

1942 16.0

1961 26.9

1980 32.8

2000 -11.4 2001 -11.1

1940 -7.1

2007 5.8

1964 16.1

1938 28.1

1927 33.4

1990 -6.0

2005 6.2

1971 16.1

1943 28.4

1991 34.7

1969 -10.9

1946 -5.9

1978 7.5

1986 16.2

1967 28.7

1995 36.8

1930 -28.5

1962 -10.2

1977 -4.3

1956 8.3

1972 16.8

2009 28.8

1945 38.1

1935 44.3

2008 -36.7

1974 -27.0

1957 -10.1

1981 -3.6

1926 9.2

2010 17.9

1989 28.9

1975 38.8

1958 45.0

1931 -43.5

1937 -34.7

2002 -21.1

1941 -10.0

1994 -0.1

1992 9.8

1988 18.0

1950 29.6

1928 38.9

1954 50.0

1933 57.1

-50% to -40%

-40% to -30%

-30% to -20%

-20% to -10%

-10% to 0%

0% to 10%

10% to 20%

20% to 30%

30% to 40%

40% to 50%

50% to 60%

Annual Return Range CRSP data provided by the Center for Research in Security Prices, University of Chicago. The CRSP 1-10 Index measures the performance of the total US stock market, which it defines as the aggregate capitalisation of all securities listed on the NYSE, AMEX and NASDAQ exchanges. Indices are not available for direct investment; therefore, their performance does not reflect the expenses associated with the management of an actual portfolio. Past performance is not a guarantee of future results. Figure 1-19

Private & Confidential

Equity Returns of Developed Markets Annual Return (%) In GBP • Stock markets performance is unpredictable and at times extreme. • Investors who follow a structured, diversified strategy are more likely to capture the returns wherever they happen to occur. 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Highest Return

Lowest Return

H.K. 84.2

Austria 121.5

Spain 115.6

Japan 12.4

Belg. 59.9

130.2 %

UK -8.2

H.K. 54.1

H.K. 63.5

H.K. 121.7

Norwa 16.9

Switz. 45.4

Spain 26.6

Switz. 50.3

Belg. 65.9

Sing. 105.4

Switz. 14.5

4.3%

Austria 5.3

Swed. 48.0

Austria 59.9

Can. 43.2

Spain 31.2

H.K. 38.9

Japan -1.8

Norwa 66.5

Swed. 38.6

Spain 74.2

Germ. 88.6

Italy 103.0

Spain 7.6

Den. 58.9

Germ. 65.1

H.K. -9.2

37.7%

Switz. 44.9

Sing. 71.8

Japan 14.9

USA 38.4

Swed. 24.1

Italy 41.2

Italy 50.8

Swed. 85.1

Can. 13.9

Austria -3.2

10.8%

Germ. 47.3

Belg. 33.8

Japan 40.1

Sing. 28.9

Germ. 33.0

Switz. -3.6

57.1%

Den. 35.4

Japan 46.4

Italy 85.8

Japan 94.4

UK 6.2

Swed. 54.4

USA 34.0

USA 31.5

Switz. 49.2

Swed. 11.9

Swed. 34.6

H.K. 20.3

Den. 40.2

Spain 48.2

Japan 66.4

Den. 11.8

Belg. -8.6

Norwa -16.2

Spain 42.5

Norwa 29.0

Austria 39.1

Norwa 27.5

Norwa 29.3

USA -13.4

Sing. 54.9

H.K. 27.7

Belg. 39.5

Switz. 64.9

Belg. 73.8

Can. -10.5

Norwa 48.3

Den. 62.5

Norwa -16.2

Sing. 28.8

Sing. 31.4

Norwa 45.3

Neth. 5.7

Spain 31.0

Norwa 16.3

USA 39.0

France 40.0

H.K. 64.3

Norwa 7.2

Spain -9.0

Italy -16.2

Austria 41.2

Swed. 27.1

Den. 38.9

Swed. 26.0

Can. 27.4

Spain -17.6

Swed. 46.1

Sing. 26.5

Neth. 38.1

France France 45.9 73.8

Den. -11.0

France 43.5

Sing. 60.6

Den. -17.5

Swed. 40.2

Italy 5.5

Neth. 28.9

Can. 16.2

Spain 30.7

USA 28.7

Can. 58.3

Italy 6.7

Norwa -9.9

Japan -18.9

Can. 39.0

Italy 23.5

Norwa 38.7

Den. 21.9

Sing. 26.2

France -21.3

H.K. 42.6

Can. 24.8

Neth. 3.7

USA -10.1

Switz. -18.9

34.4%

Den. 22.0

Switz. 29.8

Belg. 20.1

26.2%

Can. -24.5

Belg. 40.2

Japan 19.6

UK -11.8

Sing. -19.6

Den. 34.2

21.5%

29.5%

Austria 20.0

Den. 23.5

Germ. -24.9

Can. 39.0

USA 18.9

Norwa Austria 64.3 -11.5

France France 21.4 27.1

Italy 35.5

Belg. 41.6

Swed. 61.4

14.1%

42.0%

France 53.7

USA -19.4

Neth. 21.4

Neth. 26.4

Germ. 38.8

Belg. 2.4

Belg. 27.0

Neth. 15.3

Germ. 29.8

Germ. 28.0

Norwa 35.6

UK 31.9

Norwa 35.2

H.K. 52.1

Belg. -15.2

Japan 41.0

Neth. 53.3

Neth. -19.4

Den. 20.1

Belg. 21.8

Neth. 38.4

Sing. 0.9

H.K. 23.7

UK 15.2

Neth. 29.0

Switz. 22.2

France France 33.1 3.5

USA 30.9

Den. 28.5

Sing. 41.5%

Neth. -15.8

Sing. 38.8

Swed. 48.8

Switz. -22.0

UK 19.5

UK 19.1

38.3%

-0.3%

UK 22.4

USA 11.4

UK 27.8

Neth. 21.9

USA 25.6

-2.6%

Den. -12.6

Can. -21.5

Norwa 33.2

Spain 20.2

Sing. 27.6

Germ. 19.5

Spain 21.9

Sing. -27.0

Spain 27.7

18.6%

France 30.7

Neth. 28.0

38.7%

Norwa -16.9

H.K. 33.4

USA 46.8

Germ. -24.6

Switz. 19.3

Germ. 10.9

Den. 35.9

Germ. -1.0

Den. 19.9

Den. 10.1

Belg. 18.3

UK 16.5

Germ. 23.6

UK -4.3

H.K. -16.5

Belg. -23.1

France 26.1

H.K. 16.5

Neth. 27.0

France 18.2

Neth. 18.6

Den. -27.3

UK 27.6

Switz. 15.8

Norwa 25.4

Swed. 25.9

Neth. 37.2

USA -19.1

Germ. 25.6

Switz. 42.5

Belg. -25.9

Spain 19.2

Austria 10.4

Spain 32.8

Den. -1.8

Can. 19.4

France 9.6

Swed. 17.6

Swed. 12.7

21.1%

Austria -4.8

Can. -18.3

UK -23.4

H.K. 24.2

Sing. 14.0

Swed. 23.1

Italy 16.4

France 11.4

Neth. -28.2

Austria 27.5

Norwa 14.9

Austria 19.1

Spain 24.1

Germ. 31.9

Sing. -19.6

Can. 21.9

Can. 40.3

Sing. -26.5

Swed. 17.9

10.2%

Italy 31.5

Switz. -2.1

Germ. 17.5

5.3%

Can. 17.5

Den. 7.8

UK 15.8

USA -5.8

Switz. -19.3

Spain -23.4

Italy 23.9

Can. 13.9

Germ. 22.7

Neth. 15.4

UK 6.6

UK -28.4

Neth. 26.6

Austria 13.8

Germ. 18.1

UK 22.7

Austria Austria 31.3 -19.6

USA 19.3

UK 37.6

Can. -27.6

Belg. 17.2

Can. 8.6

Austria 31.1

USA -4.3

France 15.1

Germ. 2.7

France 16.6

4.9%

Den. 15.4

H.K. -7.8

Neth. -20.1

Den. -24.1

Sing. 23.7

UK 11.5

France 22.6

15.0%

Italy 4.3

Swed. -30.5

Den. 21.6

UK 12.7

Can. 14.7

H.K. 21.6

Switz. 30.0

Swed. -19.8

18.9%

Italy 34.8

France -28.3

Can. 14.5

Swed. 5.8

Japan 28.4

UK -6.9

12.2%

Italy 1.8

Norwa 10.7

Japan 3.9

Neth. 10.1

Germ. -8.7

France -20.3

H.K. -25.7

Japan 22.2

France 10.5

Belg. 21.7

UK 14.8

USA 3.7

Italy -30.6

France 17.4%

Germ. 12.3

Switz. 10.3

Japan 14.7

UK 23.7

H.K. -24.6

Spain 18.2

Belg. 32.4

Spain -28.3

Japan 12.2

Japan -2.9

UK 27.3

Can. -8.3

Sing. 7.4

Belg. 1.3

Austria Austria 5.8 -0.8

Spain 8.0

Spain -9.0

Germ. -20.3

Neth. -28.4

Belg. 21.7

Germ. 8.3

H.K. 21.0

H.K. 14.5

Switz. 3.6

31.6%

Italy 12.7

Neth. 5.4

Austral . 8.1

USA 5.1

USA 13.3

Switz. -28.8

Italy 16.0

Spain 23.9

31.4%

Germ. 11.5

Spain -3.4

Belg. 26.4

Spain -10.0

Norwa 7.0

Austria -5.5

-6.7%

H.K. -4.0

Italy 2.7

Belg. -10.1

Sing. -21.4

France -28.8

Switz. 20.6

Japan 8.0

UK 19.8

Switz. 11.9

Austria 0.5

H.K. -32.4

USA 12.4

Belg. 3.2

Swed. -1.9

Austral . -4.1

Can. 7.2

France -32.3

Switz. 10.5

23.4%

Italy -32.8

Italy 1.2

Italy -3.9

Italy 2.0

Switz. -7.5

H.K. -20.1

Can. -7.2

Switz. -4.2

Swed. -14.9

Italy -24.7

USA -30.5

UK 18.8

Switz. 7.2

USA 17.3

Can. 3.5

Swed. -1.0

Norwa y-50.4

Switz. 11.5

France -0.7

Sing. -8.4

Can. -7.8

Den. -1.3

Italy -38.1

UK 10.3

H.K. 22.3

Swed. -34.3

Austria Norwa -9.6 -4.0

Can. 20.3

Austria -11.3

Japan 1.6

Sing. -15.8

Japan -20.5

Sing. -13.8

Austria -6.4

Sing. -21.8

Swed. -25.3

Swed. -37.2

USA 15.5

Neth. 4.7

Spain 16.5

USA 0.8

Belg. -4.3

Belg. -53.5

Germ. 11.4

Italy -12.0

Den. -19.6

Sing. -37.6

Norwa -5.0

Germ. -40.8

Austria 4.7

Japan 14.8

Japan -46.8

Norwa -12.9

USA 11.7

H.K. -32.7

Austria -3.9

Japan -23.6

Sing. -27.1

Norwa -30.8

Belg. -11.7

Japan -22.3

Japan -27.6

Germ. -39.6

Neth. 15.2

USA 2.7

Italy 13.7

Japan -6.6

Japan -5.8

Austria -56.2

Japan -5.4

Spain -19.1

Den. -11.3

France France 23.7 -10.3

Source: MSCI developed markets country indices (net dividends) with at least 25 years of data. MSCI data copyright MSCI 2011, all rights reserved. This material has been distributed by Dimensional Fund Advisors Ltd., which is authorised and regulated by the Financial Services Authority. Past performance is no guarantee of future Figure 1-20 results.

Private & Confidential

Equity Returns of Developed Markets Annual Return (%) In GBP • Over this twenty-six-year period, Austria was the best performer five times, Hong Kong four times, and the UK only once. The US market was never the top performer. • Although many investors prefer to keep their capital close to home, they may pay a high price in terms of lower diversification and missed opportunity.

Boxed

is the highest return for the year.

Return

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

8.1

-4.1

38.7

-14.1

42.0

23.4

-31.4

37.7

10.2

38.3

-0.3

12.2

5.3

-6.7

4.9

21.1

-2.6

4.3

-10.8

34.4

21.5

29.5

15.0

26.2

-31.6

57.1

18.6

Austria

19.1 121.5

31.3

-19.6

4.7 130.2

-11.5

-9.6

10.4

31.1

-11.3

-3.9

-5.5

5.8

-0.8

-6.4

-4.8

-3.2

5.3

41.2

59.9

39.1

20.0

0.5

-56.2

27.5

13.8

Belgium

39.5

41.6

73.8

-15.2

59.9

32.4

-25.9

17.2

21.8

26.4

2.4

27.0

1.3

18.3

65.9

-11.7

-10.1

-8.6

-23.1

21.7

33.8

21.7

20.1

-4.3

-53.5

40.2

3.2

Canada

14.7

-7.8

7.2

-10.5

21.9

40.3

-27.6

14.5

8.6

20.3

-8.3

19.4

16.2

17.5

-7.2

58.3

13.9

-18.3

-21.5

39.0

13.9

43.2

3.5

27.4

-24.5

39.0

24.8

-19.6

28.5

-1.3

-11.0

58.9

62.5

-17.5

20.1

-11.3

35.9

-1.8

19.9

10.1

40.2

7.8

15.4

11.8

-12.6

-24.1

34.2

22.0

38.9

21.9

23.5

-27.3

21.6

35.4

France

30.7

45.9

73.8

-32.3

43.5

53.7

-28.3

21.4

27.1

23.7

-10.3

15.1

9.6

16.6

40.0

33.1

3.5

-20.3

-28.8

26.1

10.5

22.6

18.2

11.4

-21.3

17.4

-0.7

Germany

18.1

88.6

31.9

-40.8

25.6

65.1

-24.6

11.5

10.9

38.8

-1.0

17.5

2.7

29.8

28.0

23.6

-8.7

-20.3

-39.6

47.3

8.3

22.7

19.5

33.0

-24.9

11.4

12.3

Hong Kong

84.2

21.6

52.1

-24.6

33.4

22.3

-9.2

54.1

63.5 121.7

-32.7

23.7

20.3

-20.1

-4.0

64.3

-7.8

-16.5

-25.7

24.2

16.5

21.0

14.5

38.9

-32.4

42.6

27.7

Italy

35.5

85.8 103.0

-38.1

16.0

34.8

-32.8

1.2

-3.9

31.5

5.5

2.0

1.8

41.2

50.8

2.7

6.7

-24.7

-16.2

23.9

23.5

13.7

16.4

4.3

-30.6

12.7

-12.0

Japan

46.4

14.7

94.4

12.4

41.0

14.8

-46.8

12.2

-2.9

28.4

14.9

1.6

-23.6

-20.5

3.9

66.4

-22.3

-27.6

-18.9

22.2

8.0

40.1

-6.6

-5.8

-1.8

-5.4

19.6

Netherlands

38.1

28.0

37.2

-15.8

18.9

53.3

-19.4

21.4

26.4

38.4

5.7

28.9

15.3

29.0

21.9

10.1

3.7

-20.1

-28.4

15.2

4.7

27.0

15.4

18.6

-28.2

26.6

5.4

Norway

25.4

35.2

-5.0

-16.9

48.3

64.3

-16.2

-12.9

-4.0

45.3

16.9

7.0

16.3

10.7

-30.8

35.6

7.2

-9.9

-16.2

33.2

29.0

38.7

27.5

29.3

-50.4

66.5

14.9

Singapore

-8.4

-37.6

41.5

-19.6

38.8

60.6

-26.5

28.8

31.4

71.8

0.9

7.4

-15.8

-27.1

-13.8 105.4

-21.8

-21.4

-19.6

23.7

14.0

27.6

28.9

26.2

-27.0

54.9

26.5

Spain

74.2

24.1 115.6

7.6

18.2

23.9

-28.3

19.2

-3.4

32.8

-10.0

31.0

26.6

30.7

48.2

8.0

-9.0

-23.4

42.5

20.2

16.5

31.2

21.9

-17.6

27.7

-19.1

Sweden

-1.9

25.9

61.4

-19.8

54.4

48.8

-34.3

17.9

5.8

40.2

11.9

34.6

24.1

17.6

12.7

85.1

-14.9

-25.3

-37.2

48.0

27.1

23.1

26.0

-1.0

-30.5

46.1

38.6

Switzerland

10.3

64.9

30.0

-28.8

10.5

42.5

-22.0

19.3

44.9

49.2

-2.1

45.4

-7.5

50.3

22.2

-4.2

14.5

-19.3

-18.9

20.6

7.2

29.8

11.9

3.6

-3.6

11.5

15.8

31.9

22.7

23.7

6.2

10.3

37.6

-8.2

19.5

19.1

27.3

-6.9

22.4

15.2

27.8

16.5

15.8

-4.3

-11.8

-23.4

18.8

11.5

19.8

14.8

6.6

-28.4

27.6

12.7

30.9

5.1

13.3

-19.1

19.3

46.8

-19.4

34.0

31.5

11.7

-4.3

38.4

11.4

39.0

28.7

25.6

-5.8

-10.1

-30.5

15.5

2.7

17.3

0.8

3.7

-13.4

12.4

18.9

Australia

Denmark

Private & Confidential

Risk Factors Have Periods of Under- and Over-Performance 1957–2010 In GBP Value Premium

• From year to year, stocks with high book-to-market ratios and smaller market caps do not always produce higher returns. • Over longer time periods, the size and value premiums are more prevalent. • Investors that maintained disciplined size and value exposure were ultimately rewarded. • No one is certain why small cap and value stocks offer higher expected returns. But many economists assume that markets rationally discount the price of such securities to reflect higher systematic risk. • The graphs illustrate that, like the equity premium, the size and BtM premiums are frequently negative. The top graph compares performance of UK value stocks (high BtM) to UK growth stocks since 1957. The bottom graph compares small cap vs. large cap UK stocks. The blue bars denote the years in which small beat large, and value beat growth. The orange bars indicate when small and value underperformed their counterparts.

Size Premium

• Investors should not expect consistently higher returns from small cap or value stocks. If returns were reliably higher for such securities, they wouldn't be riskier.

Our source of share price and listing information was the London Share Price Database (LSPD) maintained at the London Business School. The master index of this database covers all listed stocks in the UK market since 1957. We selected stocks officially listed on the LSE and excluded foreign companies and investment trusts. To choose the value sectors we rank the universe by book-to-market and approximately the top 30% is the value universe. The small sectors, we rank the universe by market capitalisation and approximately the bottom 10% is the small universe. Copyright © 2003 Elroy Dimson, Stefan Nagel, and Garrett Quigley. UK research data provided by the London School of Business. Figure 1-22

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The Stock Market’s Reaction As Measured by the Dow Jones Industrial Average • Challenges to investment discipline also come in the form of political turmoil. • A few major bad news events of the last sixty years, tracking movement of the Dow Jones Industrial Average in the first trading day following the event—and over the following months. One obvious lesson is that the Dow did not always move as one might expect, especially in subsequent periods. • The market is a complex mechanism that factors all relevant information and expectations into securities prices. Major events do not always drive the market in predictable ways. First Trading Session Response

Subsequent Market Behaviour

Date

Event

Prior Day Close

Change

Percent Change

One Six Month Months

One Year

September 15, 2008

Lehman Declares Bankruptcy

11,421.99 10,917.51

-504.48

-4.42%

-21.43% -33.90%

-15.58%

March 19, 2003

Operation Iraqi Freedom Begins

8,194.23

8,265.45

71.22

0.87%

0.77%

16.69%

23.24%

September 11, 2001

World Trade Center towers destroyed

9,605.51

8,920.70

-684.81

-7.13%

-3.66%

11.12%

-8.71%

April 19, 1995

Oklahoma City Bombing

4,179.13

4,207.49

28.36

0.68%

3.18%

14.14%

31.56%

January 16, 1991

US launches bombing attack on Iraq

2,508.91

2,623.51

114.60

4.57%

16.97%

18.93%

29.52%

August 2, 1990

Iraq invades Kuwait

2,899.26

2,864.60

-34.66

-1.20%

-8.74%

-4.67%

4.95%

March 30, 1981

President Reagan shot by John Hinckley Jr.

994.78

992.16

-2.62

-0.26%

1.95% -14.33%

-16.90%

April 11, 1979

Iran Hostage Crisis Begins

818.94

812.63

-6.31

-0.77%

1.51%

0.45%

17.29%

August 9, 1974

President Nixon resigns

784.89

777.30

-7.59

-0.97%

-14.71%

-8.87%

5.98%

November 22, 1963

President Kennedy assassinated in Dallas

732.64

711.48

-21.16

-2.89%

6.57%

15.37%

24.99%

October 22, 1962

Cuban missile crisis

568.60

558.06

-10.54

-1.85%

15.55%

27.41%

33.89%

September 24, 1955

President Eisenhower heart attack

487.44

455.55

-31.89

-6.54%

0.04%

12.48%

5.72%

June 25, 1950

North Korea invades South Korea

224.30

213.90

-10.40

-4.64%

-4.49%

7.34%

15.13%

December 7, 1941

Japan attacks Pearl Harbor, Hawaii

115.90

112.52

-3.38

-2.92%

-0.86%

-6.19%

2.88%

Dow Jones data provided by Dow Jones Indexes. Past performance is not a guarantee of future results. Values change frequently and past performance may not be repeated. There is always the risk that an investor may lose money. Figure 1-23

Private & Confidential

UK Value vs. UK Market Monthly: July 1955–December 2010 • The following three slides underscore the importance of maintaining a long-term perspective in a structured portfolio and committing to one’s asset allocation. • This slide documents that the value effect grows stronger over longer holding periods. The chart calculates the frequency that value stocks have outperformed the overall market since 1955. This performance is calculated according to rolling time periods—from one year to forty years. • The bars in each column indicate the percentage of the time the UK value stocks outperformed the UK market for each rolling period. For example, there were 655 one-year periods (e.g., July 1955 through June 1956), 547 ten-year periods, 427 twenty-year periods and 187 forty-year periods. In these holding periods, value outperformed the UK market 70%, 99%, 100%, and 100% of the time, respectively. • Although value stocks have higher expected returns than growth stocks, investors should recognise that the record of realised returns does not assure a similar pattern in the future. • The timing and magnitude of the value premium will always be uncertain.

Rolling Time Periods

1 Year

3 Years 5 Years 10 Years 15 Years 20 Years 30 Years 40 Years

Number of Periods

655

631

607

547

487

427

307

187

Periods UK Value > UK Market

459

498

514

540

484

427

307

187

Source: UK Market is the FTSE All-Share Index. FTSE data published with the permission of FTSE. UK Value simulated by Dimensional from Bloomberg securities data, prior to 1994 data provided by London Business School. Figure 1-24

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UK Small vs. UK Market Monthly: March 1955–December 2010 • The size effect also proves itself over longer holding periods. The chart applies the same format to illustrate that risk factor compensation is also working in the small cap arena. • The bars in each column indicate the percentage of the time the UK small stocks outperformed the UK market for each rolling period. For example, between March 1955 and December 2010, there were 659 one-year holding periods, 491 fifteen-year periods, and 191 forty-year periods. In these holding periods, small cap stocks outperformed the UK market 66%, 79% and 100% of the time, respectively. • Although small company stocks have higher expected returns than large company stocks, investors should recognise that the record of realised returns does not assure a similar pattern in the future. • The timing and magnitude of the size premium will always be uncertain.

Rolling Time Periods

1 Year 3 Years 5 Years 10 Years 15 Years 20 Years 30 Years 40 Years

Number of Periods

659

635

611

551

491

431

311

191

Periods UK Value > UK Market

437

438

448

429

388

332

310

191

Source: UK Small simulated by Dimensional from StyleResearch securities data; prior to July 1981, Hoare Govett Smaller Companies Index, provided by the London School of Business. UK Market is the FTSE All-Share Index. FTSE data published with the permission of FTSE. This material has been distributed by Dimensional Fund Advisors Ltd., which is authorised and regulated by the Financial Services Authority. Past performance is no guarantee of future results. Figure 1-25

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UK Market vs. UK One-Month T-Bills Monthly: February 1955–December 2010 • The third slide in this format compares the performance of short-term fixed interest instruments to the UK market. • The bars indicate the percentage of the time that the UK market outperformed the T-bills for each rolling period. For example, the market beat T-bills in 63% of the one-year periods in 75% of the five-year periods, and in 96% of the fifteen-year periods. Equally revealing, T-bills never outperformed the market in twenty-, thirty-, and forty-year holding periods. • Although the UK market has outperformed one-month T-bills for every twenty-year period since 1955, investors should not conclude that stocks are guaranteed to outperform over every twenty-year period in the future. There is no time period over which investors can be assured of a positive equity premium—that is the nature of risk. • In summary, long-term success in the capital markets requires a long-term exposure to the risk factors that reward investors with appropriate compensation.

Rolling Time Periods

1 Year

3 Years

Number of Periods

660

636

5 Years 10 Years 15 Years 20 Years 612

552

492

432

30 Years 40 Years 312

192

Periods UK Market > UK One-Month T-Bills

415

440

462

486

473

432

312

192

Source: UK One-Month T-Bills provided by Datastream; prior to January 1975, UK Three-Month T-Bills. UK Market is the FTSE AllShare Index. FTSE data published with the permission of FTSE. This material has been distributed by Dimensional Fund Advisors Ltd., which is authorised and regulated by the Financial Services Authority. Past performance is no guarantee of future results. Figure 1-26

Private & Confidential

•

There are two primary risk factors that explain bond returns. The first is the term factor, which is the difference between the returns of long-term government bonds and short-term Treasury bills. The annual average return for the term risk factor has been 1.99% for the 80 years from 1927 to 2006.

•

The second risk factor is the default factor. It measures the difference between long-term corporate bonds and longterm government bonds, assuming that governments are less likely to default than corporations. The annual average return for the default risk factor has been 0.31% for the 80 years from 1927 to 2006.

•

Does time reduce risk?

•

First, as the investment time horizon lengthens, the actual average annual compound return achieved by a stock portfolio converges to its expected returns. As the period of measurement changes from monthly to every seven years, the volatility of returns reduces, and the existence of a losing period diminishes.

Risk Factors

Time Diversification of Risk

Does It Pay to Extend Bond Maturities Beyond 5 Yrs? No

Does It Pay to Extend Credit?

47 Years (1/1/1964 – 12/31/2010)

Quarterly: July 1983-December 2010 10% 8% 6%

Compound Returns

4% 2%

Standard Deviation

0% Quality

Government AAA

BBB High Yield

Compound Returns (%)

7.4 0

7.8 0

7.9 5

8.0 8.5 3 8

9.0 7

Standard Deviation (%)

3.5 0

3.6 9

4.1 3

4.6 4.8 3 1

8.3 4

Figure 1-6 Figure 1-5

Government rating is Barclays Capital US Government Bond Index Intermediate. AAA rating is Barclays Capital US Intermediate Credit Aaa Index. AA rating is Barclays Capital US Intermediate Credit Aa Index. A rating is Barclays Capital US Intermediate Credit A Index. BBB rating is Barclays Capital US Intermediate Credit Baa Index. High Yield rating is Barclays Capital High Yield Composite Bond Index Intermediate. Barclays Capital data, formerly Lehman Brothers, provided by Barclays Bank PLC.

Private & Confidential

• While the term provides higher expected returns, the excess returns diminish significantly beyond a term of five years as can be seen in Figure 1-6, so bonds with terms of more than five years should be avoided.

Does It Pay to Extend Maturities? 1990–2000 • Not all investors define risk as standard deviation. Some investors may seek to hedge long-term bonds. • Historically, longer maturity instruments have higher standard deviations and have not provided consistently greater returns. • Longer-term UK bonds offer higher expected returns than one-month UK bills. But the return difference is not large. From a portfolio perspective, the higher standard deviation of UK bonds is not worth taking. This suggests a move from long-term bonds to UK bills, which offer higher credit quality and a shorter maturity. • The lesson is that holding long-term fixed interest in a portfolio may not pay for itself in terms of expected reward for the high level of risk assumed.

US Equities

UK Equities

UK Bonds UK Bills

US Bonds

US Bills

0 10

Standard Deviation (%) Bonds

Bills

Equities

Annualised Compound Returns (%)

5.10

4.00

6.00

5.30

11.60

Annualised Standard Deviation (%)

3.80

2.80

12.00

8.20

21.70

19.90

Elroy Dimson, Paul Marsh and Mike Staunton, Millennium Book II: 101 Years of Investment Returns (ABN AMRO and London Business School, 2001). This publication defines the data used for the above chart and matrix as follows: UK Bills are UK One-Month Treasury Bills (FTSE). UK Bonds are the ABN AMRO Bond Index. UK Equities are the ABN AMRO/LBS Equity Index. US Bills are commercial bills 1900–1918 and One-Month US Treasury Bills (Ibbotson) 1919–2000. US Bonds are government bonds 1900–1918, the Federal Reserve Bond Index 10–15 Years 1919–1925, Long-Term Government Bonds (Ibbotson) 1926–1998, and the JP Morgan US Government Bond Index 1999–2000. US Equities are Schwert’s Index Series 1900–1925, CRSP 1-10 Deciles Index 1926–1970, and the Dow Jones Wilshire 5000 Index 1971–2000. Figure 1-17

Private & Confidential

II. Time Pickers Definition

• Time pickers, also known as market timers, believe they can predict the future direction of the market. In their efforts to time the market, they attempt to invest in stocks when the market is up and shelter their investments in cash, Treasury bills or bonds when the market hits a downturn. • Mark Hulbert, publisher of a service that objectively monitors investment newsletter performance. Hulbert’s conclusion provided a knockout blow to all 25 newsletters he tracked. None of the newsletter timers beat the market. For the 10-year period from 1988 to 1997, the time pickers’ average return was 11.06% annually, while the S&P 500 Stock Index earned 18.06% annually and the Wilshire 5000 earned 17.57% annually. • The truth is, time pickers vacillate from near zero risk to high risk and then back to zero risk again. A more rational approach for investors is to match their risk exposure to their risk capacity.

Time Pickers are Fooled by Randomness

• A New York University study completed in 1986, found no evidence that time pickers could successfully time either the beginning of a rising market or the end of a falling market. • Another IFA study examined the 2,516 stock market trading days over ten years from 1997 through 2006. The data shows that during this period, the S&P 500 Index produced an annualized return of 8.4%. Therefore, a smart and prudent investor who invested $10,000 in the S&P 500 at the beginning of 1997, and stayed fully invested was handsomely rewarded with a $12,444 gain by the end of the 10 years. • However, if just 10 trading days with the largest gains were missed, the annualized return would have dropped from 8.4% to 3.4%. Instead of gaining by $12,444, the investor would have ended with only a $3,992 gain.

• Figure 2-1 shows the benefits of buy-and-hold investing as opposed to the lunacy of time picking. This study examined the 2,516 stock market trading days for the ten-year period from 1997 to 2006. The data shows that during this period, the S&P 500 produced an annualized return of 8.4%. A smart and prudent investor who invested $10,000 in the S&P 500 at the beginning of 1997 and stayed fully invested was handsomely rewarded with a $12,444 gain by the end of 2006. Figure 2-1

Private & Confidential

Buy and Hold is Better

• In another paper written in 2002 by Professors Michael Johannes, Nicholas Polson and Jonathan Stroud market timing was once again put to the test. The simple yet powerful conclusion of this paper was that market timing strategies performed worse than the buy-and hold strategy in all cases examined. • A mere 90 days over 30 years contained 95% of all the market gains. That is an average of three days per year.

•

Smartmoney.com has been tracking these pundits dating back to 1997. Figure 2-2 summarizes some of their batting averages.

Figure 2-2

Private & Confidential

Performance of the FTSE All-Share Index January 1986–December 2010

Growth of £ 1,000

• On paper, market timing offers a seductive prospect: By predicting market direction ahead of time, a trader might capture only the best-performing days and avoid the worst. • Large gains may come in quick, unpredictable surges. A trader who misinterprets events may leave the market at the wrong time. Missing only a small fraction of days—especially the best days—can defeat a timer’s strategy. • Over a twenty-five-year period (19862010), missing the best twenty-five trading days would have cut FTSE All-Share Index annualised compound return from 10.18% to 4.75%.

Annualised Compound Return

Total Period

Missed 1 Best Day

Missed 5 Best Days

Missed 15 Best Days

Missed 25 Best Days

One-Month T-Bills

Long-Term Govt. Bonds

10.18%

9.79%

8.54%

6.46%

4.75%

6.77%

8.65%

Private & Confidential

Figure 2-3

III. Manager Selection • As Figure 3-1 clearly shows, that top performance rarely repeats in following years. Only about 14% of the top 100 managers from the oneyear periods repeated their top 100 performance in the second year. In 1999, only one of the top 100 managers made the list in 2000. • Since market returns are correlated to risk factors (not to managers), there is no reason to expect that one manager will do better than another. In addition, outstanding performance is often achieved when a mutual fund is small. • The trading and other costs generated by the investment of this much larger amount of money can neutralize or even outweigh the margin by which a mutual fund manager may beat the market in the future. • Past poor performance tends to persist in the future, primarily because of the high costs charged by many funds. • The top graph shows the rankings of 800 managers from best to worst for the first five year period from 1991 to 1995, and then maintains the first period ranking for the subsequent five years, from 1996 to 2000, to see if manager performance persisted. It came as no surprise to the researchers that what appears to be a sorting of skilled and unskilled managers in the first period turns into randomness in the subsequent period. Figure 3-1

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Is a Highly Rated Fund a Good Thing?

• Another example of the difficulty of picking a winning fund manager is found in ―Selling the Future: Concerns About the Misuse of Mutual Fund Ratings,‖ a May 16, 1994 study conducted by Lipper Analytical Services. In the study, Lipper selected highly rated mutual funds from Morningstar at the beginning of a year and then measured their performances in the following 12 months against mutual fund averages. This study was conducted in four subsequent one-year periods: 1990, 1991, 1992, and 1993.

Mutual Fund Advertisements

• Mutual fund advertisements are another source investors turn to when manager picking. Unfortunately, they convey this false message: ―Since these funds have done well in the past, they will do well in the future, so buy them today.‖ • They continue to buy and sell mutual funds based on short-term past performance falling for the implied message of mutual fund advertising.

• The Lipper study found that the majority of highly rated stock mutual funds underperformed mutual fund averages in each of the four subsequent years. This means that investors who select mutual funds from the list of highly rated funds can often end up in the wrong mutual funds at the wrong time. This not only demonstrates the unreliability of investing based on past performance over a period as short as one year, it also shows how consistently unpredictable mutual funds can be in outperforming the market. Figure 3-2

Private & Confidential

Few Consistent Equity Fund Winners Actively Managed US Equity Funds 2005-2009 • Equity funds that beat their category benchmark consistently.

• Although about 70% of the actively managed US equity funds (1,552 out of 2,231) survived the five-year period, most funds did not outperform their category benchmark. • This graph shows the percentage of funds in the surviving universe that beat their benchmark in consecutive years. In the first year (2005), 46.8% of the funds were winners, but by year five (2009), only 1% of the funds (23 out of 2,231 survivors) had consistently outperformed their benchmark.

• Additional statistics from the study reveal the inconsistency of active fund performance. On average, only 41.7% of the surviving funds beat their benchmark each year, and only 39.7% of the survivors delivered a five-year total return above their respective fund category benchmarks.

Data provided by CRSP Survivor-Bias-Free US Mutual Fund Database. Sample includes mutual funds existing as of 12/2004. Returns analyzed for the five-year period from 2005-2009. Multiple share classes are aggregated to fund level. Index funds, inverse funds, and leveraged funds are excluded. A benchmark is a standard against which the performance of an individual security or group of securities is measured. It is usually based on published indexes of securities of the same or similar class. However customized ones maybe used to suit a particular investment strategy. Past performance is not a guarantee of future results. Values change frequently, and past performance may not be repeated. There is always the risk that an investor may lose money. Figure 3-3

Private & Confidential

• Despite the strong evidence against active strategies, some people may believe that, as a group, active managers can add value. The challenge comes in identifying winning managers in advance. Some investors attempt this by choosing managers with strong past performance. • Evidence does not support their approach. In the five-year period under study, recent winners did not reliably repeat their outperformance. In fact, less than half (46%) of the funds that beat their benchmark in the preceding year did so again in the following year. Among the funds that outperformed in 2004 and 2005, only 5% beat their benchmark over the entire five years.

Non-Surviving Bond Funds Actively Managed US Bond Funds 2005-2009

Total Universe of 911 Funds in 2005

• On average, 6.5% of the actively disappeared each year.

Percentage of Cumulative Non-Survivors

managed bond fund universe

• During 2005, 7.8% of the funds had disappeared. By the fifth year, 28.5% of the fund universe (260 funds) had disappeared. • Poor investment results is one likely

reason for non-survivorship.

• Like active managers in the equity universe, bond fund managers have a significant rate of non-survival and underperformance. • As shown in this graph, of the 911 actively managed bond funds operating at the beginning of 2005, about 29% of the universe (260 funds) disappeared during the five-year period through 2009. • Some investors might assume that a 71% survival rate offered reasonable odds for choosing a winning fund over the period, with a fund’s success defined as beating the performance benchmark for its fund category. However, survival rate alone does not offer insight into a fund’s future return. Data provided by CRSP Survivor-Bias-Free US Mutual Fund Database. Sample includes mutual funds existing as of 12/2004. Returns analyzed for the five-year period from 2005-2009. Multiple share classes are aggregated to fund level. Index funds, inverse funds, and leveraged funds are excluded. A benchmark is a standard against which the performance of an individual security or group of securities is measured. It is usually based on published indexes of securities of the same or similar class. However customized ones maybe used to suit a particular investment strategy. Past performance is not a guarantee of future results. Values change frequently, and past performance may not be repeated. There is always the risk that an investor may lose money. Figure 3-4

Private & Confidential

Few Consistent Bond Fund Winners

• Even among survivors, few actively managed bond funds outperformed their category benchmark in most years or over the entire period.

Actively Managed US Bond Funds 2005-2009

• About four out of ten actively managed bond funds beat the benchmark in 2005. • Five years later, less than 1% of the surviving funds had beat the benchmark every year.

Surviving bond funds that beat their category benchmark consistently.

• Fund survival does not imply success. Although 71% actively managed funds (651 out of 911) survived the 2005-2009 period, most did not outperform their fund category benchmark. • This graph shows the percentage of bond funds in the surviving universe that beat their benchmark in consecutive years. In 2005, over 41% of the funds outperformed their respective category benchmark. By year five (2009), however, only 0.3% of the funds (3 out of the initial 1,670) had outperformed in all five years. • The study also reveals that, on average, only 30.1% of the surviving funds beat the benchmark in a given year, and over the five-year period, only 12% of surviving funds (146 out of 911) delivered a total return above their benchmark for the entire period. • Despite the strong evidence against actively managed bond funds, some investors believe that active managers as a group offer the best opportunity for long-term success, assuming these managers can be identified in advance. One approach is to buy recent winners in hopes that their outperformance will continue in the future.

• But past winners did not typically repeat over multiple years. In this fiveyear period, on average, only 42% of the funds that beat their category benchmark in the preceding year outperformed in the following year, and of the funds that outperformed in 2005 and 2006, less than 2% (7 out of 399) beat their benchmark over the entire five years.

A benchmark is a standard against which the performance of an individual security or group of securities is measured. It is usually based on published indexes of securities of the same or similar class. However customized ones maybe used to suit a particular investment strategy. Past performance is not a guarantee of future results. Values change frequently, and past performance may not be repeated. There is always the risk that an investor may lose money. Figure 3-5

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Do Winners Repeat? Subsequent Performance of Top 30 Funds, Five-Year Period: January 1986–December 1990 • The financial media and fund reporting services regularly publish lists of top-ranked mutual funds. Some investors are tempted to buy these funds in hopes of improving their portfolio returns. A broader analysis suggests that topperforming funds in one period show no reliable ability to repeat their high relative performance in a subsequent period. • During these two performance periods, most winning managers could not repeat their superior performance. Investors who chose these funds based on past returns may not have experienced similar success going forward. • This slide features the top 30 UK equity mutual funds for the five-year period from January 1986 to December 1990 and subsequent performance over the next five years (January 1991December 1995). • Only fourteen of the Top 30 funds managed to hold their superior ranking in the second five-year period. These funds were all ranked in the top half of the fund universe (quartiles 1 and 2). There were thirteen funds in the Top 30 that beat the FTSE All Share Index in the initial five-year period. However, only nine of the original Top 30 funds outperformed the index in the subsequent period.

Subsequent Period January 1991December 1995

January 1986December 1990 Fund Name Ignis Balanced Growth Inc Fidelity Special Situations M&G Recovery A Acc Premier UK Thematic A Premier Castlefield UK Alpha General Acc Fidelity Growth + Income Allianz RCM UK Equity C Aviva Investors UK Income & Gr SC1 Family Charities Ethical Tr Inc CF Canlife Growth Schroder UK Equity Inc F&C Stewardship Growth 1 Inc TU British Trust Inc L&G (Barclays) 500 Inc Reliance British Life A/I SLTM UK Equity General Inc M&G UK Select A Acc Scottish Mutual UK Equity Acc Scottish Widows UK Select Gr C Henderson UK Equity A SWIP UK Advantage A Inc Santander N&P UK Growth M&G UK Growth A Acc Lincoln Growth Trust Aviva Investors UK Equity SC1 Threadneedle UK Overseas Earnings IN Inc Pru UK Growth Trust Inc A CF Canlife General Inc Threadneedle UK Inst Inst Net GBP SWIP UK Opportunities A Top 30 Funds Average Return All Funds Average Return FTSE All-Share Index Number of Funds Number of Top 30 Funds > FTSE All-Share Index Number of All Funds > FTSE All Share Index

Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Quartile Rank 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 4

Average Annual Total Return 25.72 20.49 20.40 18.97 17.97 17.47 17.04 15.61 15.42 15.12 14.29 14.02 14.00 12.64 12.42 12.24 12.16 12.15 11.78 11.74 11.60 11.33 11.11 10.33 10.29 10.16 9.87 9.76 9.56 9.35 13.83 12.39 13.54 39

Rank 9 22 15 16 20 10 14 1 32 37 11 38 30 33 62 53 8 28 64 45 52 41 26 50 31 34 51 6 65 47

Quartile Rank 1 2 1 1 2 1 1 1 2 3 1 3 2 2 4 4 1 2 4 3 4 3 2 3 2 2 4 1 4 3

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Average Annual Total Return 18.54 16.37 17.39 17.27 16.58 18.46 17.48 24.67 15.32 15.01 17.94 14.82 15.34 15.27 12.24 13.14 18.68 15.51 11.87 13.90 13.21 14.64 16.10 13.63 15.33 15.18 13.44 20.04 11.65 13.84 15.76 15.57 16.84 67

Do Winners Repeat? Subsequent Performance of Top Thirty Funds, Five-Year Period: January 1991–December 1995 Subsequent Period January 1991December 1995 Fund Name

• This slide features the top 30 UK equity mutual funds for the fiveyear period from January 1991 to December 1995 and subsequent performance over the next five years (January 1996–December 2000). • Nine of the Top 30 funds kept their superior ranking in the second five-year period, and 21 of the funds remained in the top half of the fund universe. Also noteworthy, only seventeen managers in the original Top 30 group outperformed the FTSE All Share Index, and only eighteen funds beat the index in the following five-year period.

Rank

Aviva Investors UK Equity SC1 Artemis Capital IP UK Growth Acc Newton Income GBP Fidelity UK Growth Premier UK Thematic A Martin Currie IF UK Growth A Investec UK Special Situations A Acc Net Schroder UK Equity Inc Old Mutual UK Select Eq Acc CIS UK Growth M&G UK Select A Acc M&G Recovery A Acc Family Charities Ethical Tr Inc Jupiter UK Growth fund NFU UK Growth A Aviva Investors UK Idx Tracking SC1 UBS UK Equity Exempt F&C FTSE All-Share Tracker 1 Inc Threadneedle UK Inst Inst Net GBP Standard Life UK Equity Growth R Thornhill Cap Trust Premier Alpha Growth A Investec UK Blue Chip A Acc Net Allianz RCM UK Equity C Royal London UK Growth Insight Inv UK Discretionary A TU British Trust Inc M&G UK Growth A Acc SWIP UK Advantage A Inc Top 30 Funds Average Return All Funds Average Return FTSE All-Share Index Number of Funds Number of Top 30 Funds > FTSE All Share Index Number of All Funds > FTSE All Share Index

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Quartile Rank 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2

January 1996December 2000

Average Annual Total Return 24.67 23.89 22.77 21.22 21.03 20.04 19.66 18.68 18.54 18.46 17.94 17.80 17.63 17.48 17.39 17.27 16.90 16.73 16.71 16.58 16.37 16.37 16.37 16.22 16.12 16.10 16.08 15.51 15.41 15.34 18.04 15.57 16.84 67

Rank Quartile Rank 4 1 15 48 21 34 37 102 19 6 33 31 45 61 30 64 32 43 17 49 73 99 62 66 86 47 44 39 7 68

1 1 1 2 1 2 2 4 1 1 2 2 2 3 2 3 2 2 1 2 3 4 3 3 4 2 2 2 1 3

Source: Morningstar Direct (IMA UK All Companies sector, only funds with 5-year history used, in GBP, net returns) © Morningstar, Inc.

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Average Annual Total Return 22.33 27.61 17.98 13.79 17.06 14.95 14.67 8.27 17.23 21.11 15.00 15.32 13.98 13.21 15.33 12.83 15.15 14.24 17.38 13.70 12.47 9.81 13.16 12.80 11.21 13.83 14.04 14.47 20.82 12.70 15.21 14.23 13.9 104

Figure 3-7

Do Winners Repeat? Subsequent Performance of Top Thirty Funds, Five-Year Period: January 1996–December 2000 January 1996–December 2000

• This slide features the top 30 UK equity mutual funds for the five-year period from January 1996 to December 2000 and subsequent performance over the next five years (January 2001–December 2005). • Seven of the Top 30 funds managed to hold their superior ranking in the second five-year period, and fifteen of these original funds remained in the top half of the fund universe. All of the Top 30 funds in the first period outperformed the FTSE All Share Index, while only fourteen of the original Top 30 funds outperformed the FTSE All-Share Index in the subsequent five-year period.

Fund Name Jupiter UK Alpha Aviva Investors UK Equity SC1 Allianz RCM UK Mid Cap A Artemis Capital Allianz RCM UK Growth A Liontrust First Growth Family Asset Trust Sovereign Ethical Inc New Star UK Strategic Capital Allianz RCM UK Equity C Jupiter UK Growth fund Family Charities Ethical Tr Inc Royal London UK Growth Insight Inv UK Discretionary A Baring UK Growth JPMorgan Premier Equity Growth A Acc Aviva Investors UK Growth SC1 Acc Thornhill Cap Trust Standard Life UK Equity Growth R Smith & Williamson UK Equity Gr Trust Old Mutual UK Select Eq Acc BlackRock UK Special Situations A Acc Rensburg UK Blue Chip Growth Cavendish Opportunities Retail F&C UK Equity 1 Aberdeen UK Opportunities A Inc CIS UK Growth Ignis Balanced Growth Inc Fidelity Special Situations Fidelity Growth + Income Top 30 Funds Average Return All Funds Average Return FTSE All-Share Return Number of Funds Number of Top 30 Funds > FTSE All-Share Number of All funds > FTSE All share

Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Quartile Rank 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2

Average Annual Total Return 27.61 26.28 23.25 22.33 21.30 21.11 20.82 20.23 20.05 19.23 18.90 18.59 18.25 18.17 17.98 17.58 17.38 17.26 17.23 17.17 17.06 16.60 16.21 16.17 15.92 15.75 15.58 15.44 15.40 15.33 18.67 14.23 13.9 104 30 45

Subsequent Period January 2001–December 2005 Rank 73 154 60 116 5 3 28 142 161 10 13 95 151 1 64 163 127 156 45 150 65 55 122 102 114 61 88 41 155 15

Quartile Rank 2 4 2 3 1 1 1 4 4 1 1 3 4 1 2 4 4 4 2 4 2 2 3 3 3 2 3 1 4 1

Average Annual Total Return 1.92 -0.88 2.37 0.64 12.38 13.71 4.42 -0.22 -2.13 10.42 8.76 1.20 -0.58 14.70 2.29 -2.99 0.25 -0.94 3.44 -0.57 2.26 2.63 0.45 1.03 0.72 2.36 1.36 3.69 -0.90 7.52 2.98 2.36 2.22 167 13 66

Source: Morningstar Direct (IMA UK All Companies sector, only funds with five year history used, in GBP, net returns). Source and copyright ©1996-2008 Morningstar Limited. All rights therein are reserved, (http://www.funds.morningstar.com). Figure 3-8

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Do Winners Repeat? Subsequent Performance of Top Thirty Funds, Five-Year Period: January 2001–December 2005

• This slide features the top 30 UK equity mutual funds for a five-year period (January 2001–December 2005) and subsequent performance over the next five years (January 2006–December 2010). Only seven of the Top 30 funds managed to hold their superior ranking in the second five-year period. Sixteen of the original 30 funds remained in the top half of the fund universe and only fifteen of the original Top 30 funds managed to outperform the FTSE All-Share Index in the subsequent period. • During these two performance periods, most winning managers could not repeat their superior performance. Investors who chose these funds based on past returns may not have experienced similar success going forward. • This series offers only a limited treatment of how fund managers have performed in periods following their top ranking. The study looks at initial and subsequent fiveyear periods since 1986. Observing other time frames may provide different conclusions about the ability of fund managers to consistently deliver superior performance relative to their peers and to the broad stock market. • Perhaps most significantly, these observations suggest fund rankings have limited benefit in investment planning and analysis—and should not drive fund manager selection. © 2011 Majlis Partners

Fund Name Rathbone Recovery Fd Acc GAM UK Diversified Acc Saracen Growth Beta Fidelity Special Situations Schroder UK Mid 250 Acc IP UK Growth Acc Cavendish Opportunities Retail MFM Bowland BlackRock UK Special Situations A Acc Investec UK Special Situations A Acc Net Artemis UK Growth fund CF Walker Crips Uk Growth Inc Rensburg UK Mid Cap Growth HSBC FTSE 250 Index Retail Acc BlackRock UK A Acc Ecclesiastical UK Equity Growth A Lazard UK Alpha Retail Inc Mirabaud Mir GB Income Insight Inv UK Dynamic Mgd A Fidelity UK Aggressive Ecclesiastical Amity UK A M&G Recovery A Acc GLG UK Growth Instl Newton Income GBP Jupiter UK Growth fund Jupiter Environmental Income Acc Investec UK Alpha A Acc Net HSBC UK Growth & Income Retail Acc Artemis Capital

January 2001–December 2005 Average Annual Rank Quartile Rank Total Return 1 1 14.70 2 1 14.55 3 1 13.71 4 1 12.42 5 1 12.38 6 1 11.89 7 1 11.64 8 1 10.70 9 1 10.65 10 1 10.42 11 1 10.18 12 1 9.68 13 1 8.76 14 1 8.35 15 1 7.52 16 1 7.43 17 1 7.38 18 1 7.02 19 1 6.66 20 1 6.54 21 1 6.44 22 1 6.19 23 1 5.73 24 1 5.53 25 1 4.83 26 1 4.74 27 1 4.54 28 1 4.42 29 1 4.31

Martin Currie IF UK Growth A

Top 30 Funds Average Return All Funds Average Return FTSE All-Share Return Number of Funds Number of Top 30 Funds > FTSE All-Share Number of All funds > FTSE All share

4.23

Subsequent Period January 2006–December 2010 Average Annual Rank Quartile Rank Total Return 249 4 -10.05 167 3 3.87 77 2 6.01 185 3 3.37 134 3 4.48 54 1 6.92 75 2 6.06 17 1 8.84 85 2 5.50 132 3 4.49 229 4 1.48 56 1 6.83 15 1 9.01 237 4 0.64 49 1 7.10 36 1 7.65 4 1 13.93 126 2 4.62 169 3 3.84 10 1 10.27 162 3 3.96 11 1 10.20 154 3 4.16 78 2 6.00 181 3 3.52 238 4 0.55 176 3 3.60 29 1 7.93 200 4 2.95 8

8.45 2.36 2.22 167 30 66

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10.67 5.28 4.88 5.12 249 15 101

IV. Style Drift

Definition

• Style drift refers to the tendency of active managers and actively managed mutual funds to deviate from their stated or expected investment style. • Style drift creates numerous problems for active investors. It keeps them from maintaining reliable asset class allocations for their portfolios. This results in inconsistent exposure to risk and the resulting variations in expected average returns. • Experts widely agree that over time, asset class allocation is on average the single most important determinant of variance in investment performance. The best way to design a portfolio's asset class allocation is to use historical asset class data. • Style drift prevents an active investor from optimally reducing diversifiable risk, because the manager of a typical active fund does not remain consistently invested in the same asset class. On the surface, this does not seem to be much of a problem, but investors who reduce diversifiable risk get a bonus. The bonus is increased return. • A study by the Association for Investment Management fund that approximately 40% of actively managed funds are classified inaccurately based on the stated goals versus actual investments. • One of the reasons it is so dangerous to style drift is because future style winners are as unpredictable as stocks, times or managers.

• The lower the correlation among different indexes in a portfolio, the greater the diversification, which means lower volatility of returns. Cross Correlation among Indexes

• If indexes are highly correlated, then their prices are responding to market news in the same direction at the same time. Market news that affects prices in all markets, include the overall strength of the U.S. economy, consumer confidence, the level of interest rates and expectations for inflation rates. A low correlation means that market prices of different indexes react in different directions to the same news. These indexes have market price movements that are not connected, showing a low similarity in movement to each other.

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â&#x20AC;˘ Over the 48-year period emerging market public equities performed venture capital out, and at a lower risk level. In addition, the S&P 500 outperformed real estate by more than 50%, although the S&P 500 had about three times the risk. Figure 4-2 graphs the data from Figure 4-1 on the Markowitz risk/return plot and adds in index portfolios 5, 50 and 100 for comparison. Note where venture capital and emerging markets sit on the plot. Gold and silver are also interesting, reinforcing the idea that they have lots of risk and returns pretty close to T-bills and bonds.

Figure 4-1

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Figure 4-2

The Majlis Matrix of Style Drift: Country (Emerging) 1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

ZAF 20 % ARG 13 % CHL -3 % POL -3 % KOR -13 % HUN -17 % BRA -19 % CHN -21 % RUS -27 % IND -31 %

RUS 153 % HUN 107 % POL 59 % BRA 43 % CHN 37 % ARG 20 % IND -2 % CHL -14 % ZAF -18 % KOR -25 %

RUS 112 % HUN 95 % BRA 27 % ARG 25 % IND 11 % CHL 6% ZAF -8 % POL -22 % CHN -25 % KOR -25 %

KOR 97 % POL -7 % HUN -8 % IND -21 % ARG -24 % CHL -28 % ZAF -28 % BRA -40 % CHN -42 % RUS -83 %

RUS 247 % IND 87 % BRA 67 % ZAF 57 % CHL 39 % ARG 34 % POL 32 % CHN 13 % HUN 12 % KOR -63 %

POL -4 % BRA -11 % CHL -15 % ZAF 17 % KOR -18 % IND -22 % ARG -25 % HUN -27 % RUS -30 % CHN -31 %

KOR 137 % RUS 56 % CHL -3 % HUN -9 % BRA -17 % ZAF -17 % ARG -18 % IND -19 % CHN -25 % POL -27 %

KOR 47 % HUN 31 % ZAF 28 % RUS 16 % IND 8% POL 1% CHN -14 % CHL -20 % BRA -31 % ARG -51 %

BRA 115 % ARG 101 % CHN 88 % CHL 84 % IND 78 % RUS 76 % ZAF 46 % POL 35 % HUN 32 % KOR 6%

HUN 92 % POL 62 % ZAF 45 % BRA 36 % CHL 29 % ARG 26 % IND 19 % RUS 6% CHN 2% KOR -32 %

RUS 74 % ARG 63 % BRA 57 % IND 38 % ZAF 28 % POL 25 % CHL 22 % CHN 20 % HUN 19 % KOR -19 %

CHN 83 % ARG 67 % RUS 56 % IND 51 % BRA 46 % POL 40 % HUN 34 % CHL 29 % ZAF 21 % KOR 9%

BRA 80 % IND 73 % CHN 66 % POL 27 % RUS 25 % CHL 24 % ZAF 18 % HUN 17 % KOR 12 % ARG -4 %

KOR 38 % CHL -35 % ZAF -38 CHN -51 % ARG -54 % POL -54 % BRA -56 % HUN -62 % IND -65 % RUS -74 %

BRA 129 % RUS 105 % IND 103 % CHL 87 % HUN 78 % ARG 64 % CHN 63 % ZAF 58 % POL 43 % KOR -13 %

So urce: M scibarra

ARG

A rgentina

BRA

B razil

CHL

CHN

Chile

HUN

Hungary

China

IND

India

KOR

POL

Ko rea

RUS

P o land

ZAF

Russia

So uth A frica

Figure 4-3

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V. Silent Partners There are numerous silent partners that take a bite out of realized and unrealized gains on investments. These partners include: 1. 2. 3. 4. 5. 6. 7. 8. 9.

The sales agent or stock broker who earns a commission or load for individual stock and mutual fund trades Federal and state income tax agencies that tax realized gains The fund manager who actively invests the stocks in a mutual fund Accountants Firms that charge investment advisory fees Market makers who earn a bid-ask spread on transactions Transfer agents who handle the share transfers for all those trades Mutual fund distributors If applicable, the brokerage firm that earns interest on margin accounts

Active Investors are Unaware of all the Costs â&#x20AC;˘ The investment media, politicians, and others may convince investors that a 2.7% inflation rate is insignificant, but this rate can cut purchasing power by 26% in 10 years, 45% within 20 years, and 59% within 30 years! A 2.7% inflation rate is only negligible in very short terms; an investment purchased for $10,000 in 1970 would cost $26,094 in 2006, so it is best to buy as soon as possible and not touch that money until the last possible moment.

â&#x20AC;˘ Figure 5-1 demonstrates that on an after tax basis, the S&P 500 index fund outperformed both funds that routinely claim superior performance.

Figure 5-1

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VI. Financial Theory • Risk is most commonly measured in terms of standard deviation or the volatility around a given average.

• There are ways to refine risk and return, but at the end of the day, risk is the currency used to purchase returns. Systematic and Unsystematic Risk • When Nobel laureate William Sharpe published his Capital Asset Pricing Model (CAPM) in 1964, he decomposed a portfolio’s risk into systematic or nonspecific risk and nonsystematic or specific risk. • Systematic risk refers to the risks of the entire market as opposed to the risks specific to one stock.

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Innovations in Finance • Financial science is a relatively young academic field. But the theories, research, and applications have significantly influenced investment methodology over the last half-century. • This timeline offers some of the high points in the evolution of modern finance. Prior to 1950, conventional investment managers shunned diversification in favour of securities analysis and concentrated stock picking. • In 1952, Harry Markowitz introduced the modern investment age with his landmark work on building optimal portfolios using diversification and meanvariance analysis. The following two decades brought major developments in asset pricing and market efficiency. Conventional Wisdom circa 1950

Efficient Markets Hypothesis

“Once you attain competency, diversification is undesirable. One or two, or at most three or four, securities should be bought. Competent investors will never be satisfied beating the averages by a few small percentage points.”

The Role of Stocks James Tobin Nobel Prize in Economics, 1981 Separation Theorem: 1. Form portfolio of risky assets. 2. Temper risk by lending and borrowing.

Gerald M. Loeb, The Battle for Investment Survival, 1935

Analyse securities one by one. Focus on picking winners. Concentrate holdings to maximise returns. Broad diversification is considered undesirable.

1950

1951

1952

1953

1954

Single-Factor Asset Pricing Risk/Return Model

Eugene F. Fama, University of Chicago

William Sharpe Nobel Prize in Economics, 1990

Extensive research on stock price patterns.

Capital Asset Pricing Model: Theoretical model defines risk as volatility relative to market.

Develops Efficient Markets Hypothesis, which asserts that prices reflect values and information accurately and quickly. It is difficult if not impossible to capture returns in excess of market returns without taking greater than market levels of risk.

Shifts focus from security selection to portfolio structure.

A stock’s cost of capital (the investor’s expected return) is proportional to the stock’s risk relative to the entire stock universe.

“Liquidity Preference as Behavior Toward Risk,” Review of Economic Studies, February 1958.

Theoretical model for evaluating the risk and expected return of securities and portfolios.

1955

1956

1957

1958

1959

1960

1961

Investments and Capital Structure

Diversification and Portfolio Risk Harry Markowitz Nobel Prize in Economics, 1990

Merton Miller and Franco Modigliani Nobel Prizes in Economics, 1990 and 1985

Diversification reduces risk. Assets evaluated not by individual characteristics but by their effect on a portfolio. An optimal portfolio can be constructed to maximise return for a given standard deviation.

1962

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1964

1965

Paul Samuelson, MIT Nobel Prize in Economics, 1970 Market prices are the best estimates of value.

Theorem relating corporate finance to Price changes follow random patterns. returns. Future share prices are unpredictable. A firm’s value is unrelated to its “Proof That Properly Anticipated dividend policy. Prices Fluctuate Randomly,” Industrial Management Review, Spring 1965. Dividend policy is an unreliable guide

John McQuown, Wells Fargo Bank, 1971; Rex Sinquefield, American National Bank, 1973

Investors cannot identify superior stocks using fundamental information or price patterns.

Behaviour of Securities Prices

for stock selection.

1963

The Birth of Index Funds

1966

1967

1968

1969

Banks develop the first passive S&P 500 Index funds.

1970

First Major Study of Manager Performance Michael Jensen, 1965 A.G. Becker Corporation, 1968 First studies of mutual funds (Jensen) and of institutional plans (A.G. Becker Corp.) indicate active managers underperform indices. Becker Corp. gives rise to consulting industry with creation of “Green Book” performance tables comparing results to benchmarks.

1971

1972

1973

1974

Options Pricing Model Fischer Black, University of Chicago; Myron Scholes, University of Chicago; Robert Merton, Harvard University Nobel Prize in Economics, 1997 The development of the Options Pricing Model allows new ways to segment, quantify and manage risk.

The model spurs the development of a market for alternative investments.

Innovations in Finance Multifactor Asset Pricing Model and Value Effect

A Major Plan First Commits to Indexing

Eugene Fama and Kenneth French, University of Chicago

New York Telephone Company invests $40 million in an S&P 500 Index fund.

International Size Effect

Identifies market, size, and “value” factors in returns.

Steven L. Heston, K. Geert Rouwenhorst and Roberto E. Wessels

Analyzed NYSE stocks, 1926-1975.

Develops the three-factor asset pricing model, an invaluable asset allocation and portfolio analysis tool.

Find evidence of higher average returns to small companies in twelve international markets.

Finds that, in the long term, small companies have higher expected returns than large companies and behave differently.

“Common Risk Factors in the Returns on Stocks and Bonds,” Journal of Financial Economics 33, no. 1 (February 1993): 3-56.

“The Structure of International Stock Returns and the Integration of Capital Markets,” Journal of Empirical Finance 2, no. 3 (September 1995): 173-97.

The Size Effect

Helps launch the era of indexed investing.

Rolf Banz, University of Chicago

Burton G. Malkiel, A Random Walk Down Wall Street, 1973 ed.

1975

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

Database of Securities Prices since 1926

Variable Maturity Strategy Implemented

Nobel Prize Recognises Modern Finance

Roger Ibbotson and Rex Sinquefield, Stocks, Bonds, Bills, and Inflation

Eugene F. Fama

Economists who shaped the way we invest are recognised, emphasising the role of science in finance.

An extensive returns database for multiple asset classes is first developed and will become one of the most widely used investment databases. The first extensive, empirical basis for making asset allocation decisions changes the way investors build portfolios.

Eugene F. Fama and Kenneth R. French

Improves on the single-factor asset pricing model (CAPM).

The first major plan to index.

“Fund spokesmen are quick to point out you can’t buy the market averages. It’s time the public could.”

Integrated Equity

With no prediction of interest rates, Eugene Fama develops a method of shifting maturities that identifies optimal positions on the fixed interest yield curve.

William Sharpe for the Capital Asset Pricing Model.

Harry Markowitz for portfolio theory. “The Information in the Term Structure,” Journal of Financial Economics 13, no. 4 (December 1984): 509-28.

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Merton Miller for work on the effect of firms’ capital structure and dividend policy on their prices.

1993

1994

1995

1996

1997

1998

1999

2000

Increasing exposure to small and value companies relative to their market weights and integrating the portfolio across the full range of securities may reduce the turnover and transaction costs normally associated with forming an asset allocation from multiple components. “Migration” CRSP Working Paper No. 614, February 2007).

2001

2002

2003

2004

2005

2006

• The rise of computing power and stock return databases gave academics the tools to empirically test their theories and develop more advanced models to explain securities behaviour. • Since the 1970s, this research has led to the introduction of advanced forms of passive investing, while casting increasing doubt on the value of active management. More recently, advanced quantitative methods have given rise to the multifactor approach in portfolio construction, and integrated equity.

Fama-French Three Factor Model

•

Over 96% of the variation due to risk factor exposure.

•

After fees, traditional management typically reduces returns.

returns

96% Structured Exposure to Factors. • Market. • Size. • Value/Growth.

4% Stock Picking and Market Timing

THE MODEL TELLS THE DIFFERENCE BETWEEN INVESTING AND SPECULATING

average expected return

average excess return

[minus T-bills]

sensitivity to market [market return minus T-bills]

sensitivity to size

[small stocks minus big stocks]

sensitivity to BtM [value stocks minus growth]

random error e(t)

Priced Risk • Positive expected return. • Systematic. • Economic. • Long-term. • Investing.

Unpriced Risk • Noise. • Random.

• Short-term. • Speculating.

Source: Dimensional study (2002) of 44 institutional equity pension plans with $452 billion total assets. Factor analysis run over various time periods, averaging nine years. Total assets based on total plan dollar amounts as of year-end 2001. Average explanatory power (R2) is for the Fama/French equity benchmark universe. Figure 6-1

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The Impact of Volatility • Investors should design portfolios to experience less fluctuation in returns. Lower volatility can result in a higher compound return and greater terminal wealth. • Although Portfolio 1 experiences a strong gain in the first year, this gain is more than eliminated in year two. Portfolio 2 experiences a much smaller gain and loss during the two-year period. The lower volatility of returns produces a higher compound return and preserves more portfolio value. • Managing volatility is particularly crucial during a market downturn. After experiencing a loss, a portfolio must earn an even higher return in future periods to fully recover to its previous level.

Impact on a Hypothetical £100,000 Portfolio

Year 1 Return

Year 2 Return

Average Return

Compound Return

Value at End of Year 2

Portfolio #1

50%

-50%

-13.4%

£75,000

Portfolio #2

10%

-10%

-0.5%

£99,000 For illustrative purposes only. Figure 6-2

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VII. Footnotes

Slide 8

The Majlis Matrix • Passive Beats Active in Equities and Fixed Income 1. ―345 Equity Funds vs S&P 500 Index, 1970 - 2000 (31 Years)‖; Dead Funds and Return of Surviving Mutual Funds Relative to the Market, 1970 – 2000 (31Years) 2. ―355 Equity Funds vs S&P 500 Index, 1970-1999 (30 Years)‖; Dead Funds and Return of Surviving Mutual Funds Relative to the Market, 1970 – 1999 (30 Years); Bogle Financial Markets Research Center 3. 71 Large Cap Growth/Growth and Income Mutual Fund Managers vs. the S&P 500 Index, 1982 - 1991 (10 Years)‖; ―Is Your Alpha Big Enough to Cover Your Taxes?‖, The Journal of Portfolio Management 4. ―Large-Cap Equity Funds vs. the S&P 500 Index, 1996 - 2005 (10 Years)‖; Lipper, from Burton Malkiel’s ―A Random Walk Down Wall Street‖ 5. ―Large-Cap Equity Funds vs. the S&P 500 Index, 1986 - 2005 (20 Years)‖; Lipper, from Burton Malkiel’s ―A Random Walk Down Wall Street‖ 6. ―125 High Yield Funds vs. BarCap High Yield 2005 - 2009 (5 Years)‖; Standard & Poor’s Indices Versus Active Funds (SPIVA) Scorecard, Year-End 2009 7. ―570 Peer Bond Funds vs. Vanguard Intermediate Bond Fund, 1996 - 2006 (10 Years)‖; ―The Little Book of Common Sense Investing‖ page 143 8. ―194 Peer Bond Funds vs. Vanguard Long-Term Muni Bond Fund, 1996 - 2006 (10 Years)‖; ―The Little Book of Common Sense Investing‖ page 145 9. ―47 Government Long Funds vs. BarCap Long Government Index 2005 - 2009 (5 Years)‖; Standard & Poor’s Indices Versus Active Funds (SPIVA) Scorecard, Year- End 2009 10. ―51 Government Intermediate Funds vs. BarCap Intermediate Government Index 2005 - 2009 (5 Years)‖; Standard & Poor’s Indices Versus Active Funds (SPIVA) Scorecard, Year-End 2009 11. ―42 Government Short Funds vs. BarCap 1-3 Year Government Index 2005 - 2009 (5 Years)‖; Standard & Poor’s Indices Versus Active Funds (SPIVA) Scorecard, Year-End 2009 12. ―103 Investment-Grade Long Funds vs. BarCap Long Gov’t/Credit Index 2005 - 2009 (5 Years)‖; Standard & Poor’s Indices Versus Active Funds (SPIVA) Scorecard, Year-End 2009 13. ―60 Investment Grade Short Funds vs BarCap 1-3 Years Government, 2003 - 2008 (5 Years)‖; Standard & Poor’s Indices Versus Active Funds (SPIVA) Scorecard, Year- End 2009 14. ―81 General Municipal Debt Funds vs. S&P National AMT-Free Municipal Bond Index 2005 - 2009 (5 Years)‖; Standard & Poor’s Indices Versus Active Funds (SPIVA) Scorecard, Year-End 2009 15. ―819 Mutual Fund Managers vs. Benchmark 1962 - 2006 (45 Years)‖; ―Luck versus Skill in the Corss Section of Mutual Fund Alpha Estimates‖

Private & Confidential

Slide 12

The Majlis Matrix of Benchmark Returns ■ The Barclays Capital US Treasury 1-3yr Term Index measures the performance of short term government bonds issued by the US Treasury. For inclusion in the index, bonds must be fixed rate coupons and bullet maturity, with zero-coupon bonds and callable bonds excluded. Term indices use a standard market capitalization weighting methodology but include only bonds near to their original term rather than selecting all bonds in a maturity range. -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

■ The Barclays Capital US Treasury 10 yr Term Index measures the performance of 10 Year US Treasury Notes. The index holds 10 year notes until they fall under 7 years to maturity. For inclusion in the index, bonds must be fixed rate coupon and bullet maturity, with zero-coupon bonds and callable bonds excluded. Term indices use a standard market capitalization weighting methodology but include only bonds near to their original term rather than selecting all bonds in a maturity range ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

■ The FTSE 100 index comprises the 100 most highly capitalized blue chip companies, representing approximately 81% of the UK market. It is used extensively as a basis for investment products, such as derivatives and exchange-traded funds. -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

■ The MSCI AC (All Country) Asia Index is a free float-adjusted market capitalization weighted index that is designed to measure the equity market performance of Asia. -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

■ The MSCI EAFE Index (Europe, Australia, Asia, Far East) is a free float-adjusted market capitalization index that is designed to measure the equity market performance of developed markets, excluding the US & Canada. As of June 2007 the MSCI EAFE Index consisted of the following 21 developed market country indices: Australia, Austria, Belgium, Denmark, Finland, France, Germany, Greece, Hong Kong, Ireland, Italy, Japan, the Netherlands, New Zealand, Norway, Portugal, Singapore, Spain, Sweden, Switzerland, and the United Kingdom. -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

■ The MSCI Emerging Markets Index is a free float-adjusted market capitalization index that is designed to measure equity market performance of emerging markets. The MSCI Emerging Markets Index consisted of the following 21 emerging market country indices: Brazil, Chile, China, Colombia, Czech Republic, Egypt, Hungary, India, Indonesia, Korea, Malaysia, Mexico, Morocco, Peru, Philippines, Poland, Russia, South Africa, Taiwan, Thailand, and Turkey. -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

■ The MSCI World Index is a free float-adjusted market capitalization weighted index that is designed to measure the equity market performance of developed markets. As of June 2007 the MSCI World Index consisted of the following 23 developed market country indices: Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Greece, Hong Kong, Ireland, Italy, Japan, Netherlands, New Zealand, Norway, Portugal, Singapore, Spain, Sweden, Switzerland, the United Kingdom, and the United States. -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

■ The Nikkei 225 Stock Average is a price-weighted average of 225 top-rated Japanese companies listed in the First Section of the Tokyo Stock Exchange. -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

■ The Philadelphia Stock Exchange Gold and Silver Index is a capitalization weighted index which includes the leading companies involved in the mining of gold and silver. -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

■ The S&P 500 has been widely regarded as the best single gauge of the large cap U.S. equities market since the index was first published in 1957. The index has over US$ 4.83 trillion benchmarked, with index assets comprising approximately US$ 1.1 trillion of this total. The index includes 500 leading companies in leading industries of the U.S. economy, capturing 75% coverage of U.S. equities.

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The Majlis Matrix of Hedge Fund Benchmark Returns

Slide 13

■ The Barclay Convertible Arbitrage Index represents hedged investing in the convertible securities of a company. A typical investment is to be long the convertible bond and short the common stock of the same company. Positions are designed to generate profits from the fixed income security as well as the short sale of stock, while protecting principal from market moves. --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- -------------------------------------------------------------------------------------------------------■ The Barclay Distressed Securities Index represents debt, equity and/or trade claims of companies undergoing financial distress or currently in default already. The securities of companies in distressed or defaulted situations typically trade at substantial discounts to par value due to difficulties in analyzing a proper value for such securities, lack of street coverage, or simply an inability on behalf of traditional investors to accurately value such claims or direct their legal interests during restructuring proceedings. --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- -------------------------------------------------------------------------------------------------------■ The Barclay Event Driven Index strategy is defined as 'special situations' investing designed to capture price movement generated by a significant pending corporate event such as a merger, corporate restructuring, liquidation, bankruptcy or reorganization. ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------■ The Barclay Fixed Income Arbitrage Index strategy aims to profit from price anomalies between related interest rate securities. Most managers trade globally with a goal of generating steady returns with low volatility. This category includes interest rate swap arbitrage, US and non-US government bond arbitrage and forward yield curve arbitrage. ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------■ The Barclay Fund of Funds Index is a measure of the average return of all FoFs in the Barclay database. The index is simply the arithmetic average of the net returns of all the FoFs that have reported that month. ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------■ The Barclay Hedge Fund Index is a measure of the average return of all hedge funds (excluding Funds of Funds) in the Barclay database. The index is simply the arithmetic average of the net returns of all the funds that have reported that month. ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------■ The Barclay Merger Arbitrage Index represents funds that typically invest simultaneously long and short in the companies involved in a merger or acquisition. Risk arbitrageurs are typically long the stock of the company being acquired and short the stock of the acquirer. By shorting the stock of the acquirer, the manager hedges out market risk, and isolates his exposure to the outcome of the announced deal. ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------■ The Barclay Multi-Strategy Index represents funds that are characterized by their ability to dynamically allocate capital among strategies falling within several traditional hedge fund disciplines. The use of many strategies, and the ability to reallocate capital between them in response to market opportunities, means that such funds are not easily assigned to any traditional category. ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------■ The Dow Jones Credit Suisse Global Macro Hedge Fund Index is a subset of the Dow Jones Credit Suisse Hedge Fund Index that measures the aggregate performance of global macro funds. Global macro funds typically focus on identifying extreme price valuations and leverage is often applied on the anticipated price movements in equity, currency, interest rate and commodity markets. Managers typically employ a top-down global approach to concentrate on forecasting how political trends and global macroeconomic events affect the valuation of financial instruments. Profits can be made by correctly anticipating price movements in global markets and having the flexibility to use a broad investment mandate, with the ability to hold positions in practically any market with any instrument. These approaches may be systematic trend following models, or discretionary. ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------■ The Dow Jones Credit Suisse Long/Short Equity Hedge Fund Index is a subset of the Dow Jones Credit Suisse Hedge Fund Index that measures the aggregate performance of long/short equity funds. Long/short equity funds typically invest in both long and short sides of equity markets, generally focusing on diversifying or hedging across particular sectors, regions or market capitalizations. Managers typically have the flexibility to shift from value to growth; small to medium to large capitalization stocks; and net long to net short. Managers can also trade equity futures and options as well as equity related securities and debt or build portfolios that are more concentrated than traditional long-only equity funds. ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------■ The Dow Jones Credit Suisse Managed Futures Hedge Fund Index is a subset of the Dow Jones Credit Suisse Hedge Fund Index that measures the aggregate performance of managed futures funds. Managed futures funds (often referred to as CTAs or Commodity Trading Advisors) typically focus on investing in listed bond, equity, commodity futures and currency markets, globally. Managers tend to employ systematic trading programs that largely rely upon historical price data and market trends. A significant amount of leverage may be employed since the strategy involves the use of futures contracts. CTAs tend not to have a particular bias towards being net long or net short any particular market. ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------■ The Eurekahedge EM HF Index belongs to funds which guides to emerging market hedge funds. A consolidated database of emerging market mandates and strategies, it covers the regions including: Emerging Markets, Asia ex Japan, Greater China, India, Korea, Taiwan, Eastern Europe & Russia, Middle East & Africa, Brazil, Argentina, Latin America. ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------■ The Eurekahedge Fund of Funds Index ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------■ The Eurekahedge Hedge Funds are investment vehicles that explicitly pursue absolute returns on their underlying investments. The appellation "Absolute Return Fund" would be more accurate, not least as not all hedge funds maintain an explicit hedge on their portfolio of investments. However the "Hedge Fund" definition has come to incorporate any absolute return fund investing within the financial markets (stocks, bonds, commodities, currencies, derivatives, etc) and/or applying nontraditional portfolio management techniques including, but not restricted to, shorting, leveraging, arbitrage, swaps, etc. Hedge funds can invest in any number of strategies and they are perhaps most readily identifiable by their structure, which is typically a limited partnership (the manager acting as the general partner and investors acting as the limited partners) with performance related fees, high minimum investment requirements and restrictions on types of investor, entry and exit periods. ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------■ The Eurekahedge Islamic Fund Index The Eurekahedge Global Islamic Fund Database is the largest fund research engine for the Islamic finance industry, with unmatched coverage across the asset classes and across the globe. Our Islamic fund database represents a collection of more than 679 investment products, all compliant with Shariah guidelines, and provides access to close to 90% of that universe. ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------■ The Eurekahedge Long-Only Abs. Ret. Funds are not beholden to any index benchmark. In contrast to traditional long-only mutual funds, the flexibility and diverse portfolio construction of this latest entrant in the hedge fund universe help to align the over-riding interest of investors and managers: to generate superior positive returns. ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------■ The MSCI Emerging Markets Index is a free float-adjusted market capitalization index that is designed to measure equity market performance of emerging markets. The MSCI Emerging Markets Index consisted of the following 21 emerging market country indices: Brazil, Chile, China, Colombia, Czech Republic, Egypt, Hungary, India, Indonesia, Korea, Malaysia, Mexico, Morocco, Peru, Philippines, Poland, Russia, South Africa, Taiwan, Thailand, and Turkey.

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