Equity Opportunity Long Short

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Equity Opportunity Long Short
Concentrated Alpha Equity
Max Anderl
Head of Concentrated Alpha Equity Team
January 2017
Summary
• No change in team and philosophy
• Following many years of strong performance, 2016 was very disappointing.
• Company specific earnings development appeared to matter less than macro calls with high factor
correlations
• The market was very news flow/story driven: Recession, recovery, Brexit fraction, Opec, US elections,
inflation/bond yields, value/growth
• Trump's election win has changed growth and inflation expectations and moved bond yields and metal
prices up as markets believe in a strong stimulus program
• As always we continue to own companies on the long side where we see shareholder value creation and
short where value is destroyed
• While this has worked very well in the last couple of years it was a fruitless exercise as macro plays and ETF
flows dominated the picture. We expect this to normalise in 2017.
1
The Concentrated Alpha investment process
3 Circle Investment Process – In use since inception in 2004
3 Circle Research Process
Portfolio Construction
& Risk Management
Fundamental
Qualitative
Quantitative
•
Bottom up stock selection process
•
Independent long and short
portfolio
•
Balanced and diversified portfolio
•
Positions weighted according
to risk reward considerations
•
Longs 1 to 3%; Shorts -1 to -3%
Client portfolio
• Approx ~150 - 200
stocks
For illustrative purposes only
2
Equity Opportunity Long Short
Equity Opportunity Long Short I-B-acc historical performance
200
190
Fund Performance (NAV)
180
170
160
150
140
130
120
110
Apr 14 Jun 14 Aug 14 Okt 14 Dez 14 Feb 15 Apr 15 Jun 15 Aug 15 Okt 15 Dez 15 Feb 16 Apr 16 Jun 16 Aug 16 Okt 16
Equity Opportunity Long Short I-B-acc (LHS)
Source: Factset, UBS Asset Management. Fund performance is gross of Fees in EUR. Data as at 30 December 2016.
Note: Past performance is not indicative of future performance.
3
Equity Opportunity Long Short strategy
Performance attribution by sector: YTD to 30 December 2016
Fund
Weight
Contribution
Consumer Discretionary
-3.8
-1.4
Consumer Staples
12.7
-1.3
Energy
-0.4
0.6
Financials
1.8
0.4
Health Care
21.9
-1.3
Industrials
-16.4
-6.3
Information Technology
7.6
0.1
Materials
-5.7
-5.1
Real Estate
0.9
-0.4
Telecom Services
-0.7
-0.4
Utilities
1.5
0.1
Group
Source: Wilshire, UBS Asset Management
Data is indicative only and will not necessarily add up to total fund return due to calculation methodology
4
Market very speculative
1,3
29
1,2
25
1,1
21
1,0
17
0,9
13
EPS
Relative P/E
Forward P/E – MSCI Europe Materials vs MSCI Europe
0,8
2012
9
2013
2014
Relative Forward P/E Materials vs. MSCI Europe (LHS)
2015
2016
MSCI Materials EPS (RHS)
Source: Factset, as at 30 December 2016. EPS: Earnings Per Share.
5
QE has pushed investors out of bonds into other
asset classes
CFTC non-commercial long – short positions
Source: Bloomberg, Bernstein Analysis, as at 19 November 2016. CFTC = Commodity Futures Trading Commission
6
Commodity futures trading
Contracts on the Shanghai and Dalian futures exchanges
Source: Gavekal Data/Macrobond, as at 30 November 2016
7
Chinese speculative money everywhere,
even in the Bitcoin
Chinese Yuan accounts for 98% of bitcoin trading
Source: CLSA, 29 December 2016
8
Peak valuations in capital goods
European capital goods 12-month rolling consensus EV/EBIT
16x
14x
12x
10x
8x
6x
4x
99
00
01
02
03
04
05
06
07
Europe Coverage
08
09
10
11
12
13
14
15
16
Historical Avg.
Source: UBS estimates, Datastream as at 30 December 2016
9
China stabilising thanks to stimulus
Infrastructure investment led the recovery
A rapid slide in private sector investment
45,0
30,0
40,0
25,0
35,0
30,0
20,0
25,0
15,0
20,0
15,0
10,0
10,0
5,0
5,0
0,0
Q1 2012
Q1 2013
Manufacture
Q1 2014
Real Estate
Q1 2015
Q1 2016
Infrastructure
0,0
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Total Urban
State Owned Enterprises
Private Enterprises
Source: Datastream, as at 30 December 2016
10
Consumer Staples and Health Care vs. Yields
Diversion between bond proxy sectors and yields has increased
300,0
-0,2
260,0
0,3
220,0
0,8
180,0
1,3
140,0
1,8
100,0
Jan 12
Jan 13
MSCI Europe Cons Stples
Jan 14
MSCI Europe Health Care
Jan 15
Jan 16
Inverted 10Y German Yield
Source: Factset, as at 30 December 2016. Inverted yield calculated by 1 less 10 year German yield.
11
European industrials company
Total return relative to earnings
Price-to-earnings vs history
130,0
35,0
120,0
23,0
21,0
30,0
110,0
19,0
25,0
100,0
17,0
90,0
20,0
15,0
80,0
15,0
70,0
60,0
2014
FY1 Earnings
2015
FY2 Earnings
10,0
2017
2016
Total Return (RHS)
13,0
11,0
2014
2015
PE
2016
2017
10Y Avg PE
Source: Factset, as at 30 December 2016. Earnings estimates rebased to 100.
12
Pernod Ricard
Total return relative to earnings
Price-to-earnings vs history
120,0
130,0
22,0
115,0
120,0
21,0
110,0
110,0
20,0
19,0
105,0
100,0
18,0
100,0
90,0
95,0
80,0
90,0
2014
FY1 Earnings
2015
70,0
2017
2016
FY2 Earnings
Total Return (RHS)
17,0
16,0
15,0
2013
2014
PE
2015
2016
10Y Avg PE
Source: Factset, as at 30 December 2016. Earnings estimates rebased to 100.
13
GSK
Total return relative to earnings
Price-to-earnings vs history
22,0
105,0
19,0
21,0
100,0
18,0
20,0
95,0
19,0
90,0
18,0
17,0
16,0
17,0
85,0
16,0
80,0
15,0
75,0
15,0
14,0
14,0
70,0
13,0
65,0
2014
FY1 Earnings
2015
FY2 Earnings
12,0
2017
2016
Total Return (RHS)
13,0
12,0
2014
2015
PE
2016
2017
10Y Avg PE
Source: Factset, as at 30 December 2016. Earnings estimates rebased to 100.
14
Global GDP Growth
6,0
5,0
4,0
3,0
2,0
1,0
0,0
-1,0
-2,0
-3,0
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
Global GDP Growth YoY
Source: Factset, as at 30 December 2016
15
Cyclical Sectors Relative to Defensive
Dislocation between fundamentals of cyclical sectors and returns
Cyclicals EPS vs Defensives
116,0
116,0
112,0
112,0
108,0
108,0
104,0
104,0
100,0
100,0
96,0
96,0
92,0
Dez 15
Mrz 16
Jun 16
Sep 16
Dez 16
92,0
Dez 15
MSCI World Cyclicals '16e EPS vs Defensives ($, rebased)
MSCI World Cyclicals vs Defensives
Mrz 16
Jun 16
Sep 16
Dez 16
MSCI Europe Cyclicals '16e EPS vs Defensives (€, rebased)
MSCI Europe Cyclicals vs Defensives
Source: Factset, as at 30 December 2016 and JPMorgan as at 10 October 2016. All MSCI data rebased to 100.
16
Inflation Expectations
US five year inflation expectation
2,5
2,4
2,3
Trump Election Victory
2,2
2,1
2,0
1,9
1,8
Nov 15
Feb 16
Mai 16
Aug 16
US Dollar Inflation Swap Forward 5Y5Y
Source: Factset, as at 30 December 2016
17
Factor correlations
Stock correlation is falling but factor correlation at all-time high
Source: MSCI, Factset, IBES, Bernstein analysis, as at 19 November 2016.
Global L/S Factors: Comp Value, 12 Price Momentum, Quality, Composite Growth. We use rolling correlation of absolute returns of long-short factors and correlations of (signed) returns of
stocks.
18
Trump story
Strong rotation and flows post election
Widest weekly flow disparity between bond and equity ever recorded
• Record ETF equity inflow but outflow in mutual funds
• Record inflow in financials
• Record Emerging Market debt outflow
• Biggest bond and precious metal outflows in 3.5 years
Record Inflows to financial sector fund
Record outflows from EM debt funds
Source: BofAML, as at 17 November 2016.
19
Trump: returning to Reagan boom?
Can we expect the 1980s style boom that some have suggested
• Demographics
–
1980s: 1.6% GDP growth driven by workforce of baby boomers and generation X
–
2016: 0.2% growth driven by ageing population and shrinking working age population
• Workforce
–
1980s: record number of women entering labour market and 25-34 year olds living at home at an all time low
–
2016: share of women in labour force shrinking and proportion of 25-34 year olds living at home has doubled
• Economy
–
1980s: emerging from recession, double digit inflation, 8% unemployment, double digit inflation peaking at 20%,
low productivity and high market volatility
–
2016: seven years removed from recession, inflation <2%, unemployment <5%, low interest rates, structurally low
productivity, low market volatility
• Debt
–
1989: federal debt 31% of GDP and doubled by 1992
–
2016: federal debt 105% of GDP, highest level other than WW2
• Market
–
1989: recent extended bear markets. Schiller CAPE 6.6%
–
2016: extended bull markets. Schiller CAPE 27.2%
Source: Hedgeye Demography, 2016.
20
Impact of ECB action
Euro area bank lending rates
Euro area: cost of new bank loans to private sector
Cost of new bank loans to real economy
Source: ECB, JPMorgan, as at 31 October 2016
Source: ECB, JPMorgan, as at 31 October 2016
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Why?
What is value?
Source: Bernstein, as at 26 September 2016.
22
Equity Opportunity Long Short Fund
Portfolio construction as at 31 December 2016
Top 10 holdings
Reckitt Benckiser
Unilever
Chevron
Alphabet
Ingredion
Total
Pernod Ricard
Nordea Bank
Relx
Fresenius
%
2.5
2.4
2.4
2.4
2.2
2.2
2.2
2.1
2.1
2.1
Sectors
Health Care
Consumer Staples
18,71
-3,17
Information Technology
-1,11
Financials
19,07
8,17
-9,85
Utilities
-3,23
Real Estate
0,00
Energy
-8,14
Telecommunication Services
-3,84
Materials
-5,03
Consumer Discretionary
-14,80
13,68
5,96
2,65
7,87
3,01
0,87
7,26
Industrials -23,94
Gross & net long/short exposure
Long exposure
Short exposure
Gross exposure
Net exposure
0,00
+97.9%
-73.1%
+171.0%
+24.8%
Region
-2,1%
Asia + JP
North America
Europe + UK
EM
Source: UBS Asset Management.
This information should not be construed as a recommendation to buy or sell any particular security.
10,61
1,2%
-8,7%
27,7%
68,9%
-58,9%
-3,5%
0,2%
Long
Short
23
Distribution Partner Team
Clemens W. Bertram
Head Distribution Partners
Andrew Hinrichsen
Steffen Hoelscher
Tel. +49-69-1369 5484
[email protected]
Tel. +49-69-1369 5315
[email protected]
Tel. +49-69-1369 5318
[email protected]
Lothar Traub
Alexander A. Werani
Tel. +49-89-20609 5114
[email protected]
Tel. +49-69-1369 5104
[email protected]
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