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Credit Suisse Research Institute February 2017
Global Investment Returns Yearbook 2017 - Slide Deck Elroy Dimson, Paul Marsh and Mike Staunton | London Business School Richard Kersley, Michael O'Sullivan | Credit Suisse
From past to present: the evolution of equity markets 100%
6
Others
13
Chn Swi 2½ Aus 3
Can
5 6
Aut Rus 75% Net 12 Fra
9 7
Jap
50% 13 Ger 25
25%
UK
58
USA
15
0% 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
US
UK
Jap
Ger
Fra
Can
Aus
Net
Swi
Rus
Aut
Chn
Others
The continuing dominance of the USA is a striking feature Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research
3
From past to present: the USA’s great transformation Health
Banks
Oil & gas
Banks
Retail
Rail
Rail dominated USA in 1900
Other industrial
Iron, coal steel
Other financial
Other industrial
Insurance Media
Utilities
Tobacco Telegraph Other transport Other Food
Start-1900
Technology Other
Utilities Telecoms Travel & leisure Drinks
Start-2017
80% by weight in industries now small or non-existent then small or non-existent 67% by weight in industries Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research
4
From past to present: the UK’s great transformation Health
Banks Mines
Mines Tobacco
Banks
Insurance Rail
Textiles
Rail dominated UK in 1900
Iron, coal steel
Drinks
Other
Other industrial Utilities Telegraph Insurance
Start-1900
Telecoms Oil & gas
Utilities Media
Other industrial
Other financial Travel & leisure Retail Other Drinks
Start-2017
Disruptive technology has been familiar for two centuries Investing in the “new” is not the obvious route to riches Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research
5
The past: Real returns and dividends, 1900–2016 10,000
United States
1,000
United Kingdom 513
1,402
1,000
Reinvested dividends 11.9
100
10
100
10
Reinvested divi8.1 dends 3.3 2.7
9.8
2.6 1
0.10 1900 10 20 30 40 50 60 70 80 90 2000 10 Equities: return 6.4% p.a. Bonds 2.0% p.a.
Equities: capital gain 2.1% p.a. Bills 0.8% p.a.
1
0.10 1900 10 20 30 40 50 60 70 80 90 2000 10
Equities: return 5.5% p.a. Bonds 1.8% p.a.
Equities: capital gain 0.8% p.a. Bills 1.0% p.a.
We should focus on real return. Real return is largely dividends. Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research
6
Long-run asset returns for all countries, 1900–2016 Annualized real return (%)
6
6.4
5.1
4
4.3
2 0 Aut Ita Bel Fra Ger Prt Spa Jap Eur Nor WxU Ire Swi Net Wld Den Fin UK Can Swe NZ US Aus SAf -2 -4
Equities -6
Bonds
Bills
Historical equity risk vs. bonds = 3.2%
Historical equity risk vs. bills = 4.2%
Prospectively, the world equity (versus bills) is 3–3½%
Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research
7
US equities were volatile with large real drawdowns 0%
-10% -20%
-30% -40% -50%
-60% -70%
-80%
Bonds Equities
But bonds have also had large drawdowns in real Diversification across asset classes helps to reduce risk Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research
8
The present: Yields on sovereign bills and bonds (%) 4
3
Since In 2016 the 2016 rates hit low,all-time rates have low risen
2 1 0 -1 Swi Ger Net Swe Bel Fra Fin Aut Den Ire Spa Jap Spa Ita Por UK US Can Nor Aus Ita Jap 3-months
10 years
20 years
But long rates still low. So short rates likely to remain low
Real (after inflation) returns on long bonds still very low Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research
9
The race to zero and beyond? Is it over? Real yield for representative 10-year index-linked bond 4
3 2
1 0 -1
-2
00
01 US
02 UK
03
04 Fra
05
06 Ger
07
08 Jap
09
10 Can
11
12 Swe
13
14
15
16
17
Average
No need to extrapolate past returns. Just look at current yields Real yields still negative or close to zero. Slight upturn recently Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 10
Low real interest rates means a low return world Real rate of return (%) 10
-10
5.2
4.2
5.2 1.4
1.4
0
-5
9.0
7.6
5
0.1
-3.4
4.6
2.2
2.8
9.4
11.0
9.8
5.6
4.0
-2.2
- 5.4 -10.0 -11
-15 Low 5%
Next 15% Next 15% Next 15% Next 15% Next 15% Next 15%
Top 5%
Percentiles of real interest rates across 2,317 country -years
Equities next 5 years % p.a.
Bonds next 5 years % p.a.
Real interest rate boundary %
Real interest rates impact subsequent real equity and bond returns
Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 11
Many investors are anticipating a return to “normal” 300 years of UK bond yields. What yield is “normal”? 20 15 10 5
4.5
1.9 0 Long-run average
The high bond returns since 1980 were not “normal” Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 12
Many investors are anticipating a return to “normal” Average annual % real interest rate (short-term interest rate minus inflation) 4 3.9 3.1 3.2
2 0
2.2 0.7 0.4
-0.7 -0.5
-0.9 -0.6
0.9 1.2 0.1 0.3
-1.6 -1.7
-2 1900–1980
-4 USA
UK
Europe
1981–2008
2009–2016
All years
All Yearbook
What real rate of interest is “normal”?
Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 13
Inflation on the rise? Equities, bonds and inflation Rate of return/inflation (%) 20
19
19.1
10
12.2
12.0
8.0
0
10.9
10.9 5.3
0.4
4.2
1.7
2.62.7
7.1
-3.5
7.7 4.2
5.9 -4.5
2.0
-11.6
-10 -22.7
-20 -30
Low 5% Next 15% Next 15% Next 15% Next 15% Next 15% Next 15% Top 5% Percentiles of inflation across 2,453 country-years; bond and equity returns in same year
Real bond returns (%)
Real equity returns (%)
Inflation rate boundary (%)
Equities best during low inflation. Bonds better in deflation. Higher inflation harms bonds – but it also harms equities. Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 14
Equities have been a poor inflation hedge Real equity return 150%
100%
50%
Sensitivity to concurrent inflation was −0.52
0%
-50%
-100% -30% UK
US
0% Ger
Jap
Net
Fra
30% Ita
Swi
Aus
Can
60% Swe
Den
Spa
Bel
90%year Inflation in same Ire
SAf
Nor
NZ
Fin
Don’t confuse inflation beating with inflation hedging
Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 15
The future: What equity can we expect? Annualised (% p.a.)
5
5.1
0.5
0.5
4
4.1
0.8
3
3.3
2 1
0 Historical equity Real dividend real return growth
Change in P/D ratio
Average dividend yield
Treasury bill return
Expected equity risk
We estimate the long-run equity vs bills to be 3–3½%
Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 16
The high return world we grew up in Annualized real returns on equities and bonds (%)
8 6 4
2 0
US
Jap
UK Can Aus Since 1950 Baby boomers
Eur
Wld Equities
US Jap Bonds
UK Can Aus Since 1980
Eur Wld
Generation X
Millennials? Past performance conditions our aspirations Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 17
Looking forward from 2017 Annualized real returns on equities and bonds (%) 6 4 2 0 -2
World since 1950
World since 1980
Historical high returns
World
Equities
USA
Japan
UK
Europe
Bonds
Emerging markets
Prospective lower returns
Have expectations changed? We are still in a lower return world Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 18
The future Real interest rates are low, and bond yields are low – expected returns on all assets are lower than past returns – modest rises in inflation are unlikely to impact real returns
Long-run equity (vs bills) is around 3–3½% – lower than the historical average
– equities will stay volatile, but diversification lowers risk
What to do about the low-return world? – the Yearbook provides a long-term perspective – the current ‘vogue’ is to seek returns from smart beta… Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 19
Investors ditching active management (USA, 2007–16) Cumulati ve asset flow (USD bn)
Sources: Investment Company Institute, Simfund, Credit Suisse
20
Rapid growth of factor-based ETFs Smart beta assets under management USD bn 500
400
300
200
100
0
2012
13
14
Source: Financial Times, Morningstar Direct
15
16
21
Are investment institutions adopting smart beta? 75% now using or actively evaluating smart beta Among s, two-thirds considering further allocation 20% now use ≥ 5 smart beta indexes (vs 2% in 2014)
22
The smart-beta “zoo” Researchers have reported on 458 factors – few will work out-of-sample
Fama-French identify five factors – market, size, value, profitability, investment – others stress low-risk, and momentum
We study five factors – low-risk, momentum, size, value, income
– over up to 117 years, and in up to 23 markets
Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 23
Low-risk investing Classic strategy (published 1972) – low beta portfolio gives superior risk-adjusted return – now labelled as BAB (Bet Against Beta)
Recent approach uses idiosyncratic volatility – low-volatility portfolio gives superior return… – … compared to high-volatility portfolio
Many variants of these “low-vol” strategies – an approach that has become popular since the GFC
Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 24
Low risk factors in the USA, 1963–2016 1,000 247 216 212 122
100
9.7 8.8
10
1
0.10 Low specific risk 10.9% p.a. High specific risk 4.1% p.a.
Low variance 10.6% p.a. High variance 4.3% p.a.
Weakest effect: “Betting against beta” beta”.
Low beta 10.5% p.a. High beta 9.4% p.a.
Strongest: Specific risk
Source: Data from Professor Kenneth French, Dartmouth (website)
25
Specific risk factor in the USA 1,000
469 318 247 233
100
10
8.8
1
0.10 Lowest risk 10.9% p.a. Higher risk 11.4% p.a.
Lower risk 10.7% p.a. Highest risk 4.1% p.a.
Medium risk 12.2% p.a.
arises from underperformance of the highest-risk quintile
Based on daily returns. Source: Data from Professor Kenneth French, Dartmouth (website)
26
Specific risk factor in the UK 100 35.9 24.9
10 3.9
1
0.10 Lowest risk 11.6% p.a.
Medium risk 10.3% p.a.
Highest risk 4.2% p.a.
Same methodology using daily data: UK results similar to USA
Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 27
Longer-term (60-month) specific risk estimates in UK 1,000
623 571 282
100
10
1 Lowest risk 12.0% p.a.
Medium risk 11.8% p.a.
Highest risk 10.4% p.a.
Effect driven entirely by highest risk stocks during dot-com crash
Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 28
Momentum
Sort stocks by return over past 6 or 12 months — target the top and bottom quintile (say)
Wait a month — then buy past winners (and short past losers)
Rebalance periodically — typically after 6, 3 or 1 month(s)
Measure : WML (“Winner Minus Loser”)
Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 29
The momentum , 1900*–2016 United States†
United Kingdom‡ 10,000,000
10,000,000 2,131,993
1,000,000
5,043,966
1,000,000 100,000
100,000
10,000
10,000
3,634
1,000
1,000
100
100
10
Cumulative difference between winners and losers 7.4%
1
61
10 1 0.10 1900 10
0.10
Winner 17.5% per year
Loser 9.5% per year
Cumulative difference between winners and losers 10.4% 20
30
40
Winner 14.1% per year
50
60
70
80
90 2000 10
Loser 3.6% per year
Large long-run, pre-cost returns; but volatile with high turnover * from 1926 in the US
†
Based on a 6/1/6 momentum strategy
‡
Based on a 12/1/1 momentum strategy
Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 30
Momentum returns around the world Winner minus loser returns, % per month 1.5
1.0 .71
.79
0.5
0.0
-0.5 Jap Chi Rus Spa US Can Aus Swe Prt Fra Aut Avg Ger Neth Ita Bel Swi Fin Ire UK Nor Den NZ SAf Griffin, Ji & Martin: to end-2000
Full period to end-2016 (updated by Dimson, Marsh & Staunton)
Unusually, the factor was larger after the original study Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 31
Other factors: the size , 1926*–2015 100,000
United States
United Kingdom
100,000 53,263 33,879
10,000
27,256
10,000
6,861
4,690
3,220 1,000
1,087
1,000 100
100 10
10
1
0.10 26 30 35 40 45 50 55 60 65 70 75 80 85 90 95 00 05 10 15 Micro-caps 12.7% per year Larger-caps 9.7% per year
Small-caps 12.1% per year
1 1955 60
65
70
75
80
Micro-caps 17.9% per year Mid-caps 13.9% per year
85
90
95 2000 05
10
15
Small-caps 15.3% per year Large-caps 12.0% per year
The smallest firms have performed the best, but not consistently * from 1955 in the UK
Sources: US CRSP capitalization deciles are from Morningstar; UK Small and Mid-caps are Numis indices
32
The size effect around the world % per month (small minus large)
0.8
.45 0.4
.32
0.0
-0.4 Nor Net Fin NZ Ita Den SAf Spa Chi UK Bel Swe Ger US Avg Swi Can Aus Rus Jap Por Ire Aut Fra Longer term
2000 to 2016
A global phenomenon; large since 2000 Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 33
Other factors: the value , 1926*–2016 United Kingdom
United States 10,000
100,000
9,173
56,247 10,000
Value
4,274 3,061
Value
1,000
1,146
1,000
419
100
100
10
Growth
Growth
10 1
0.10 26 30 35 40 45 50 55 60 65 70 75 80 85 90 95 00 05 10 15 High book-to-market 12.9% p.a. Low book-to-market 9.3% p.a.
US market 9.8% p.a.
1 1955 60
65
70
75
80
High book-to-market 16.0% p.a. Low book-to-market 10.3% p.a.
85
90
95 2000 05
10
15
UK market 12.1% p.a.
Value stocks have outperformed, but not always * from 1955 in the UK
Source: US data from Professor Kenneth French, Dartmouth (website)
34
The value effect around the world % per year (value minus growth) 10
5 2.1 2.5
0
-5
-10 Ire Fin Den Swi Ita Por NZ US Bel Ger UK Spa Wld Fra SAf Net Swe Can Aus Aut Nor Jap Chi Rus Longer term
Since 2000
Value beat growth in most countries over the long-run
Source: MSCI value and growth indexes
35
Other factors: the income , 1900*–2016 United Kingdom
United States 1,000,000
100,000 13,991
10,000
7,156
158,727
100,000
35,966
2,312 1,451
1,000
10,000
100
1,000
10
100
1
10
0.10 End
1 1900 10
6,810
20
30
High yield 11.3% p.a.
Medium yield 10.4% p.a.
High yield 10.8% p.a.
Low yield 9.0% p.a.
Zero yield 8.5% p.a.
Low yield 7.8% p.a.
40
50
60
70
80
90 2000 10
UK market 9.4% p.a.
High yielders have beaten low yielders; a variant of the value effect * from 1927 in the USA
Source: US data from Professor Kenneth French, Dartmouth (website)
36
The income around the world Yield (% per year) 15 10
6.2 5
3.9
0 -5
-10 NZ
Ire Bel Swi US Ger UK
Longer term
Ita Den Fin Avg Spa Sin Can HK Net Aus Fra Nor Jap Swe Aut
Since 2000
Positive premia in most countries; large premia since 2000
Source: All data except UK data is from Professor Kenneth French, Dartmouth (website)
37
Factor performance since the financial crisis USA Highest
Lowest
2008
2009
2010
2011
2012
2013
2014
2015
2016
2008–16
Low vol 90.3 Income 20.7 Momentum –2.4 Size –4.3 Value –6.0
Size 28.5 Value –8.0 Income –17.2 Low vol –33.0 Momentum –50.6
Size 13.6 Momentum 8.5 Income 7.1 Value –4.5 Low vol –15.2
Low vol 40.5 Income 29.5 Momentum 1.4 Size –3.7 Value –12.8
Value 11.5 Size 7.8 Momentum –0.9 Low vol –1.5 Income –7.6
Size 5.3 Value 4.7 Momentum 4.5 Income –8.2 Low vol –9.3
Low vol 11.3 Income 1.6 Value –2.2 Momentum –5.3 Size –6.7
Momentum 42.3 Low vol 13.9 Income 2.4 Size –9.3 Value –12.0
Value 17.2 Income 14.8 Size 9.6 Low vol –1.8 Momentum –22.4
Low vol 6.0 Size 4.0 Income 3.8 Value –1.8 Momentum –6.0
Low vol 127.0 Momentum 78.8 Income 15.7 Value –11.8 Size –17.5
Size 24.9 Income 1.1 Value –6.9 Low vol –20.1 Momentum –25.4
Size 12.4 Value 3.2 Momentum 0.7 Income –13.7 Low vol –22.9
Low vol 35.0 Income 28.3 Momentum 20.6 Size –4.9 Value –10.7
Size 17.0 Value 14.8 Momentum –1.7 Income –8.1 Low vol –15.7
Momentum 32.4 Size 15.5 Low vol 11.5 Income 0.0 Value 0.0
Momentum 42.8 Size 12.1 Income –1.3 Low vol –6.2 Value –10.0
Low vol 23.7 Momentum 20.1 Size 11.1 Income –11.2 Value –20.9
Value 20.2 Income 15.3 Size –4.9 Momentum –18.3 Low vol –21.2
Momentum 12.8 Size 6.5 Low vol 5.5 Income 2.1 Value –3.2
UK Highest
Lowest
Differences over time and across markets; scope to diversify
Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 38
Smart beta Distinguish factors vs s — factor: an influence on security returns — : a superior expected return
s may be evident over the long run — some (size, value) may be harvested ively — some (low-vol, momentum) require portfolio churning
Factor exposures can have a large performance impact — investors can unwittingly take large positions
Factors can become too expensive — popularity can make them an over-crowded trade
Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 39
Global Investment Returns Yearbook 2017 - Slide Deck Elroy Dimson, Paul Marsh and Mike Staunton | London Business School Richard Kersley, Michael O'Sullivan | Credit Suisse
From past to present: the evolution of equity markets 100%
6
Others
13
Chn Swi 2½ Aus 3
Can
5 6
Aut Rus 75% Net 12 Fra
9 7
Jap
50% 13 Ger 25
25%
UK
58
USA
15
0% 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
US
UK
Jap
Ger
Fra
Can
Aus
Net
Swi
Rus
Aut
Chn
Others
The continuing dominance of the USA is a striking feature Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research
3
From past to present: the USA’s great transformation Health
Banks
Oil & gas
Banks
Retail
Rail
Rail dominated USA in 1900
Other industrial
Iron, coal steel
Other financial
Other industrial
Insurance Media
Utilities
Tobacco Telegraph Other transport Other Food
Start-1900
Technology Other
Utilities Telecoms Travel & leisure Drinks
Start-2017
80% by weight in industries now small or non-existent then small or non-existent 67% by weight in industries Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research
4
From past to present: the UK’s great transformation Health
Banks Mines
Mines Tobacco
Banks
Insurance Rail
Textiles
Rail dominated UK in 1900
Iron, coal steel
Drinks
Other
Other industrial Utilities Telegraph Insurance
Start-1900
Telecoms Oil & gas
Utilities Media
Other industrial
Other financial Travel & leisure Retail Other Drinks
Start-2017
Disruptive technology has been familiar for two centuries Investing in the “new” is not the obvious route to riches Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research
5
The past: Real returns and dividends, 1900–2016 10,000
United States
1,000
United Kingdom 513
1,402
1,000
Reinvested dividends 11.9
100
10
100
10
Reinvested divi8.1 dends 3.3 2.7
9.8
2.6 1
0.10 1900 10 20 30 40 50 60 70 80 90 2000 10 Equities: return 6.4% p.a. Bonds 2.0% p.a.
Equities: capital gain 2.1% p.a. Bills 0.8% p.a.
1
0.10 1900 10 20 30 40 50 60 70 80 90 2000 10
Equities: return 5.5% p.a. Bonds 1.8% p.a.
Equities: capital gain 0.8% p.a. Bills 1.0% p.a.
We should focus on real return. Real return is largely dividends. Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research
6
Long-run asset returns for all countries, 1900–2016 Annualized real return (%)
6
6.4
5.1
4
4.3
2 0 Aut Ita Bel Fra Ger Prt Spa Jap Eur Nor WxU Ire Swi Net Wld Den Fin UK Can Swe NZ US Aus SAf -2 -4
Equities -6
Bonds
Bills
Historical equity risk vs. bonds = 3.2%
Historical equity risk vs. bills = 4.2%
Prospectively, the world equity (versus bills) is 3–3½%
Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research
7
US equities were volatile with large real drawdowns 0%
-10% -20%
-30% -40% -50%
-60% -70%
-80%
Bonds Equities
But bonds have also had large drawdowns in real Diversification across asset classes helps to reduce risk Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research
8
The present: Yields on sovereign bills and bonds (%) 4
3
Since In 2016 the 2016 rates hit low,all-time rates have low risen
2 1 0 -1 Swi Ger Net Swe Bel Fra Fin Aut Den Ire Spa Jap Spa Ita Por UK US Can Nor Aus Ita Jap 3-months
10 years
20 years
But long rates still low. So short rates likely to remain low
Real (after inflation) returns on long bonds still very low Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research
9
The race to zero and beyond? Is it over? Real yield for representative 10-year index-linked bond 4
3 2
1 0 -1
-2
00
01 US
02 UK
03
04 Fra
05
06 Ger
07
08 Jap
09
10 Can
11
12 Swe
13
14
15
16
17
Average
No need to extrapolate past returns. Just look at current yields Real yields still negative or close to zero. Slight upturn recently Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 10
Low real interest rates means a low return world Real rate of return (%) 10
-10
5.2
4.2
5.2 1.4
1.4
0
-5
9.0
7.6
5
0.1
-3.4
4.6
2.2
2.8
9.4
11.0
9.8
5.6
4.0
-2.2
- 5.4 -10.0 -11
-15 Low 5%
Next 15% Next 15% Next 15% Next 15% Next 15% Next 15%
Top 5%
Percentiles of real interest rates across 2,317 country -years
Equities next 5 years % p.a.
Bonds next 5 years % p.a.
Real interest rate boundary %
Real interest rates impact subsequent real equity and bond returns
Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 11
Many investors are anticipating a return to “normal” 300 years of UK bond yields. What yield is “normal”? 20 15 10 5
4.5
1.9 0 Long-run average
The high bond returns since 1980 were not “normal” Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 12
Many investors are anticipating a return to “normal” Average annual % real interest rate (short-term interest rate minus inflation) 4 3.9 3.1 3.2
2 0
2.2 0.7 0.4
-0.7 -0.5
-0.9 -0.6
0.9 1.2 0.1 0.3
-1.6 -1.7
-2 1900–1980
-4 USA
UK
Europe
1981–2008
2009–2016
All years
All Yearbook
What real rate of interest is “normal”?
Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 13
Inflation on the rise? Equities, bonds and inflation Rate of return/inflation (%) 20
19
19.1
10
12.2
12.0
8.0
0
10.9
10.9 5.3
0.4
4.2
1.7
2.62.7
7.1
-3.5
7.7 4.2
5.9 -4.5
2.0
-11.6
-10 -22.7
-20 -30
Low 5% Next 15% Next 15% Next 15% Next 15% Next 15% Next 15% Top 5% Percentiles of inflation across 2,453 country-years; bond and equity returns in same year
Real bond returns (%)
Real equity returns (%)
Inflation rate boundary (%)
Equities best during low inflation. Bonds better in deflation. Higher inflation harms bonds – but it also harms equities. Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 14
Equities have been a poor inflation hedge Real equity return 150%
100%
50%
Sensitivity to concurrent inflation was −0.52
0%
-50%
-100% -30% UK
US
0% Ger
Jap
Net
Fra
30% Ita
Swi
Aus
Can
60% Swe
Den
Spa
Bel
90%year Inflation in same Ire
SAf
Nor
NZ
Fin
Don’t confuse inflation beating with inflation hedging
Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 15
The future: What equity can we expect? Annualised (% p.a.)
5
5.1
0.5
0.5
4
4.1
0.8
3
3.3
2 1
0 Historical equity Real dividend real return growth
Change in P/D ratio
Average dividend yield
Treasury bill return
Expected equity risk
We estimate the long-run equity vs bills to be 3–3½%
Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 16
The high return world we grew up in Annualized real returns on equities and bonds (%)
8 6 4
2 0
US
Jap
UK Can Aus Since 1950 Baby boomers
Eur
Wld Equities
US Jap Bonds
UK Can Aus Since 1980
Eur Wld
Generation X
Millennials? Past performance conditions our aspirations Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 17
Looking forward from 2017 Annualized real returns on equities and bonds (%) 6 4 2 0 -2
World since 1950
World since 1980
Historical high returns
World
Equities
USA
Japan
UK
Europe
Bonds
Emerging markets
Prospective lower returns
Have expectations changed? We are still in a lower return world Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 18
The future Real interest rates are low, and bond yields are low – expected returns on all assets are lower than past returns – modest rises in inflation are unlikely to impact real returns
Long-run equity (vs bills) is around 3–3½% – lower than the historical average
– equities will stay volatile, but diversification lowers risk
What to do about the low-return world? – the Yearbook provides a long-term perspective – the current ‘vogue’ is to seek returns from smart beta… Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 19
Investors ditching active management (USA, 2007–16) Cumulati ve asset flow (USD bn)
Sources: Investment Company Institute, Simfund, Credit Suisse
20
Rapid growth of factor-based ETFs Smart beta assets under management USD bn 500
400
300
200
100
0
2012
13
14
Source: Financial Times, Morningstar Direct
15
16
21
Are investment institutions adopting smart beta? 75% now using or actively evaluating smart beta Among s, two-thirds considering further allocation 20% now use ≥ 5 smart beta indexes (vs 2% in 2014)
22
The smart-beta “zoo” Researchers have reported on 458 factors – few will work out-of-sample
Fama-French identify five factors – market, size, value, profitability, investment – others stress low-risk, and momentum
We study five factors – low-risk, momentum, size, value, income
– over up to 117 years, and in up to 23 markets
Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 23
Low-risk investing Classic strategy (published 1972) – low beta portfolio gives superior risk-adjusted return – now labelled as BAB (Bet Against Beta)
Recent approach uses idiosyncratic volatility – low-volatility portfolio gives superior return… – … compared to high-volatility portfolio
Many variants of these “low-vol” strategies – an approach that has become popular since the GFC
Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 24
Low risk factors in the USA, 1963–2016 1,000 247 216 212 122
100
9.7 8.8
10
1
0.10 Low specific risk 10.9% p.a. High specific risk 4.1% p.a.
Low variance 10.6% p.a. High variance 4.3% p.a.
Weakest effect: “Betting against beta” beta”.
Low beta 10.5% p.a. High beta 9.4% p.a.
Strongest: Specific risk
Source: Data from Professor Kenneth French, Dartmouth (website)
25
Specific risk factor in the USA 1,000
469 318 247 233
100
10
8.8
1
0.10 Lowest risk 10.9% p.a. Higher risk 11.4% p.a.
Lower risk 10.7% p.a. Highest risk 4.1% p.a.
Medium risk 12.2% p.a.
arises from underperformance of the highest-risk quintile
Based on daily returns. Source: Data from Professor Kenneth French, Dartmouth (website)
26
Specific risk factor in the UK 100 35.9 24.9
10 3.9
1
0.10 Lowest risk 11.6% p.a.
Medium risk 10.3% p.a.
Highest risk 4.2% p.a.
Same methodology using daily data: UK results similar to USA
Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 27
Longer-term (60-month) specific risk estimates in UK 1,000
623 571 282
100
10
1 Lowest risk 12.0% p.a.
Medium risk 11.8% p.a.
Highest risk 10.4% p.a.
Effect driven entirely by highest risk stocks during dot-com crash
Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 28
Momentum
Sort stocks by return over past 6 or 12 months — target the top and bottom quintile (say)
Wait a month — then buy past winners (and short past losers)
Rebalance periodically — typically after 6, 3 or 1 month(s)
Measure : WML (“Winner Minus Loser”)
Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 29
The momentum , 1900*–2016 United States†
United Kingdom‡ 10,000,000
10,000,000 2,131,993
1,000,000
5,043,966
1,000,000 100,000
100,000
10,000
10,000
3,634
1,000
1,000
100
100
10
Cumulative difference between winners and losers 7.4%
1
61
10 1 0.10 1900 10
0.10
Winner 17.5% per year
Loser 9.5% per year
Cumulative difference between winners and losers 10.4% 20
30
40
Winner 14.1% per year
50
60
70
80
90 2000 10
Loser 3.6% per year
Large long-run, pre-cost returns; but volatile with high turnover * from 1926 in the US
†
Based on a 6/1/6 momentum strategy
‡
Based on a 12/1/1 momentum strategy
Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 30
Momentum returns around the world Winner minus loser returns, % per month 1.5
1.0 .71
.79
0.5
0.0
-0.5 Jap Chi Rus Spa US Can Aus Swe Prt Fra Aut Avg Ger Neth Ita Bel Swi Fin Ire UK Nor Den NZ SAf Griffin, Ji & Martin: to end-2000
Full period to end-2016 (updated by Dimson, Marsh & Staunton)
Unusually, the factor was larger after the original study Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 31
Other factors: the size , 1926*–2015 100,000
United States
United Kingdom
100,000 53,263 33,879
10,000
27,256
10,000
6,861
4,690
3,220 1,000
1,087
1,000 100
100 10
10
1
0.10 26 30 35 40 45 50 55 60 65 70 75 80 85 90 95 00 05 10 15 Micro-caps 12.7% per year Larger-caps 9.7% per year
Small-caps 12.1% per year
1 1955 60
65
70
75
80
Micro-caps 17.9% per year Mid-caps 13.9% per year
85
90
95 2000 05
10
15
Small-caps 15.3% per year Large-caps 12.0% per year
The smallest firms have performed the best, but not consistently * from 1955 in the UK
Sources: US CRSP capitalization deciles are from Morningstar; UK Small and Mid-caps are Numis indices
32
The size effect around the world % per month (small minus large)
0.8
.45 0.4
.32
0.0
-0.4 Nor Net Fin NZ Ita Den SAf Spa Chi UK Bel Swe Ger US Avg Swi Can Aus Rus Jap Por Ire Aut Fra Longer term
2000 to 2016
A global phenomenon; large since 2000 Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 33
Other factors: the value , 1926*–2016 United Kingdom
United States 10,000
100,000
9,173
56,247 10,000
Value
4,274 3,061
Value
1,000
1,146
1,000
419
100
100
10
Growth
Growth
10 1
0.10 26 30 35 40 45 50 55 60 65 70 75 80 85 90 95 00 05 10 15 High book-to-market 12.9% p.a. Low book-to-market 9.3% p.a.
US market 9.8% p.a.
1 1955 60
65
70
75
80
High book-to-market 16.0% p.a. Low book-to-market 10.3% p.a.
85
90
95 2000 05
10
15
UK market 12.1% p.a.
Value stocks have outperformed, but not always * from 1955 in the UK
Source: US data from Professor Kenneth French, Dartmouth (website)
34
The value effect around the world % per year (value minus growth) 10
5 2.1 2.5
0
-5
-10 Ire Fin Den Swi Ita Por NZ US Bel Ger UK Spa Wld Fra SAf Net Swe Can Aus Aut Nor Jap Chi Rus Longer term
Since 2000
Value beat growth in most countries over the long-run
Source: MSCI value and growth indexes
35
Other factors: the income , 1900*–2016 United Kingdom
United States 1,000,000
100,000 13,991
10,000
7,156
158,727
100,000
35,966
2,312 1,451
1,000
10,000
100
1,000
10
100
1
10
0.10 End
1 1900 10
6,810
20
30
High yield 11.3% p.a.
Medium yield 10.4% p.a.
High yield 10.8% p.a.
Low yield 9.0% p.a.
Zero yield 8.5% p.a.
Low yield 7.8% p.a.
40
50
60
70
80
90 2000 10
UK market 9.4% p.a.
High yielders have beaten low yielders; a variant of the value effect * from 1927 in the USA
Source: US data from Professor Kenneth French, Dartmouth (website)
36
The income around the world Yield (% per year) 15 10
6.2 5
3.9
0 -5
-10 NZ
Ire Bel Swi US Ger UK
Longer term
Ita Den Fin Avg Spa Sin Can HK Net Aus Fra Nor Jap Swe Aut
Since 2000
Positive premia in most countries; large premia since 2000
Source: All data except UK data is from Professor Kenneth French, Dartmouth (website)
37
Factor performance since the financial crisis USA Highest
Lowest
2008
2009
2010
2011
2012
2013
2014
2015
2016
2008–16
Low vol 90.3 Income 20.7 Momentum –2.4 Size –4.3 Value –6.0
Size 28.5 Value –8.0 Income –17.2 Low vol –33.0 Momentum –50.6
Size 13.6 Momentum 8.5 Income 7.1 Value –4.5 Low vol –15.2
Low vol 40.5 Income 29.5 Momentum 1.4 Size –3.7 Value –12.8
Value 11.5 Size 7.8 Momentum –0.9 Low vol –1.5 Income –7.6
Size 5.3 Value 4.7 Momentum 4.5 Income –8.2 Low vol –9.3
Low vol 11.3 Income 1.6 Value –2.2 Momentum –5.3 Size –6.7
Momentum 42.3 Low vol 13.9 Income 2.4 Size –9.3 Value –12.0
Value 17.2 Income 14.8 Size 9.6 Low vol –1.8 Momentum –22.4
Low vol 6.0 Size 4.0 Income 3.8 Value –1.8 Momentum –6.0
Low vol 127.0 Momentum 78.8 Income 15.7 Value –11.8 Size –17.5
Size 24.9 Income 1.1 Value –6.9 Low vol –20.1 Momentum –25.4
Size 12.4 Value 3.2 Momentum 0.7 Income –13.7 Low vol –22.9
Low vol 35.0 Income 28.3 Momentum 20.6 Size –4.9 Value –10.7
Size 17.0 Value 14.8 Momentum –1.7 Income –8.1 Low vol –15.7
Momentum 32.4 Size 15.5 Low vol 11.5 Income 0.0 Value 0.0
Momentum 42.8 Size 12.1 Income –1.3 Low vol –6.2 Value –10.0
Low vol 23.7 Momentum 20.1 Size 11.1 Income –11.2 Value –20.9
Value 20.2 Income 15.3 Size –4.9 Momentum –18.3 Low vol –21.2
Momentum 12.8 Size 6.5 Low vol 5.5 Income 2.1 Value –3.2
UK Highest
Lowest
Differences over time and across markets; scope to diversify
Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 38
Smart beta Distinguish factors vs s — factor: an influence on security returns — : a superior expected return
s may be evident over the long run — some (size, value) may be harvested ively — some (low-vol, momentum) require portfolio churning
Factor exposures can have a large performance impact — investors can unwittingly take large positions
Factors can become too expensive — popularity can make them an over-crowded trade
Source: Elroy Dimson, Paul Marsh, and Mike Staunton, Triumph of the Optimists, Princeton University Press, 2002, and subsequent research 39
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