Factor Investing
in China – A look at A-shares
Yogesh Padmanabhan
Portfolio Manager & Head of Best Styles EM strategies
JP Morgan Macro Quantitative Conference
Hong Kong
February 2017
For Institutional/Professional Investor use only. Not for public distribution
2
About Allianz Global Investors
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AuM by asset class
Equity
EUR 139 bn
(29%)
Fixed Income**
EUR 207 bn
(43%)
Multi Asset
EUR 118 bn
(25%)
Alternatives
EUR 17 bn (3%)
Owned by Allianz SE – one of the world’s largest and most financially robust organizations
AuM of EUR 481bn * across Equity, Fixed Income, Multi Asset and Alternatives
25 locations worldwide – global investment and research capabilities with consultative local delivery
600+ investment professionals , 10+ years average tenure of Portfolio Managers, 550+ relationship managers
Our clients benefit from our global resources and deep understanding of investments
* As at 30 September 2016. Source: Allianz Global Investors. Any differences in totals are due to rounding. ** Includes money market.
3
Best Styles @ Allianz Global Investors
Systematic Equity is one of the leading providers of systematic investment solutions
o Successful Systematic Equity management since 1996
o USD 41bn AuM in Systematic Equity products, whereof USD 1.3bn in Best Styles Emerging Markets assets*
o One of the longest track records in the industry for factor investing with Best Styles Global Developed running since 1999
o Strong Performance:
Best Styles Global outperformed the benchmark in each five year rolling period since its inception in 1999
Best Styles Global Developed Best Styles Europe Best Styles Emerging Markets
-40
-20
0
20
40
60
80
100
120
140
-40 -20 0 20 40 60 80 100 120 140
Be
st S
tyle
s G
lob
al D
evelo
ped
MSCI WORLD Total Return (Net)
COMP0189Outperformance in 157 of 1575-year periods as at 31/12/2016
-40
-20
0
20
40
60
80
100
120
140
-40 -20 0 20 40 60 80 100 120 140
Be
st S
tyle
s E
uro
pe
MSCI EUROPE WEIGHTED
COMP0405Outperformance in 132 of 1325-year periods as at 31/12/2016
-40
-20
0
20
40
60
80
100
120
140
-40 -20 0 20 40 60 80 100 120 140
Be
st S
tyle
s E
uro
pe
MSCI EUROPE WEIGHTED
COMP0405Outperformance in 132 of 1325-year periods as at 31/12/2016
-30
-20
-10
0
10
20
30
-30 -20 -10 0 10 20 30
Be
st S
tyle
s E
merg
ing
Mar
ket
s
MSCI Emerging Markets Total Return (Net)
COMP0190Outperformance in 30 of 30
3-year periods as at 31/12/2016
Stable outperformance of all systematic Best Styles equity composites since inceptions
Past performance is not a reliable indicator of future results. Unless otherwise noted, index returns are presented as total returns, which reflect both price performance and income from dividend payments, if any, but do not reflect fees, brokerage
commissions or other expenses of investing. Please see the Appendix for additional disclosures and GIPS ® presentation for the composite presented above. Please also consider the risks and notes at the end of the presentation. Figures gross
of fees. Please also consider the risks and notes at the end of the presentation.
Source: IDS; data as of 31/12/2016, preliminary data in USD.
4
What is China Equity ?
Shanghai A-shares Shenzhen A-shares HK-listed China
stocks US-listed ADRs
Total Market Cap (USD bn)
4254 3301 4121 1404
Number of stocks 1211 1895 980 162
Number of stocks with Avg. Daily Traded Value >
US$ 10m 910 1383 80 27
Total
13079
4248
2400
0
5
10
15
20
25
30
35
40
45
Shanghai Shenzhen HK-Listed stocks US-listed ADRs
USD
bn
Average daily traded value (US$ bn )
Source: Allianz Global Investors, HSBC. As at January 31 2017.
5
China is very dynamic with quick changes in market sentiment Shanghai Composite has had twice as many down years in the last 25 years vs. S&P500
Shanghai Composite has had 12 down years
compared with 6 for the S&P500 in the last 25 years
Shanghai Composite has had 5 down years vs. 2 for
the S&P500 in the last 10 years
Retail investors have a large presence in China,
providing liquidity, and contributing to large swings
Large breadth, large depth make China a good
testing ground for quantitative investing
Risk management is critical to survive the bouts of
volatility
Shanghai Composite S&P500
1991 129.4% 26.3%
1992 166.6% 4.5%
1993 6.8% 7.1%
1994 -22.3% -1.5%
1995 -14.3% 34.1%
1996 65.1% 20.3%
1997 30.2% 31.0%
1998 -4.0% 26.7%
1999 19.2% 19.5%
2000 51.7% -10.1%
2001 -20.6% -13.0%
2002 -17.5% -23.4%
2003 10.3% 26.4%
2004 -15.4% 9.0%
2005 -8.3% 3.0%
2006 130.4% 13.6%
2007 96.7% 3.5%
2008 -65.4% -38.5%
2009 80.0% 23.5%
2010 -14.3% 12.8%
2011 -21.7% 0.0%
2012 3.2% 13.4%
2013 -6.7% 29.6%
2014 52.9% 11.4%
2015 9.4% -0.7%
2016 -12.3% 9.5%
2017 (YTD) 1.7% 2.5%
Source: Allianz Global Investors, Bloomberg, data as of 31st January 2017
6
Performance success of factors in China A-Shares
Excess Return and Tracking Error for typical stock selection criteria
rev 6m sy
rev 3m
upgrades 3m cps growth
by
upgrades 1m
dps growth
ey 12m tr
ey 12m fwd
rev 1m
dy 12m fwd
cy
upgrades 6m
op-cy
eps growth
payout
roe
gross margin
by 12m fwd
12m ex 3m momentum
rnoa
merton
evebitda change in roe
debtasset netmarg
24m ex 3m momentum
ebitint
12m ex 1m momentum
trailing eps growth 5y
1m mean reversion
3m mean reversion
6m mean reversion
12m mean reversion
LowVol
breadth of earnings estimates
4%
9%
-5% 0% 5% 10%
perf
orm
an
ce s
tab
ilit
y
(Tra
ckin
g E
rror
in %
p.a
.)
Relative Return (p.a.)
Stable excess
returns
High excess
returns
Source: AllianzGI, 2004-201612, relative performance of the most attractive top 20% of the factor, implemented on a sector neutral basis vs. an equal weighted benchmark.
Calculations performed by the portfolio management team. Not independently verified.
Revisions
Quality
Value
Momentum
Growth
Mean
Reversion
7
Correlation analysis of single factors
Source: AllianzGI, 2004-201612, relative performance of the most attractive top 20% of the factor, implemented on a sector neutral basis vs. an equally weighted benchmark.
Calculations performed by the portfolio management team. Not independently verified.
sy ey by cy evebitda
op_cy
by_12m_fw
d
ey12m_tr
dy_12m_fw
d
ey_12m_fw
d
reversi
on_1m
reversi
on_3m
reversi
on_6m
reversi
on_12m
debtass
et
highvol
eps_gro
wth
cps_
grow
th
dps_gro
wth
trailin
g_eps_gro
wth_5y
upgrades_
3m
upgrades_
1m
upgrades_
6m
rev6
rev3
rev1
rnoa
roe
payout
net_m
argin
gross
_marg
in
merto
n
ebitint
change_in
_roe
mom
entum
_12x1m
mom
entum
_12x3m
mom
entum
_24x3m
sy 1.00 0.58 0.58 0.74 0.59 0.61 0.53 0.59 0.47 0.55 -0.07 0.27 0.31 0.34 0.08 -0.26 -0.37 0.10 -0.03 -0.08 0.00 0.22 0.08 -0.31 -0.31 -0.16 -0.02 -0.10 0.10 -0.41 -0.32 -0.18 -0.11 -0.23 -0.42 -0.37 -0.43
ey 0.58 1.00 0.41 0.68 0.71 0.51 0.53 0.88 0.54 0.83 0.06 0.32 0.36 0.29 0.06 -0.08 -0.32 0.13 -0.02 0.13 0.18 0.09 0.28 -0.21 -0.11 -0.04 0.22 0.24 0.23 -0.20 -0.20 -0.19 0.02 -0.13 -0.34 -0.23 -0.23
by 0.58 0.41 1.00 0.71 0.53 0.61 0.59 0.39 0.08 0.26 -0.09 0.07 0.10 0.27 0.16 -0.29 -0.43 -0.18 -0.35 -0.40 -0.29 0.21 -0.22 -0.45 -0.44 -0.31 -0.43 -0.43 -0.21 -0.39 -0.40 -0.45 -0.49 -0.27 -0.45 -0.45 -0.58
cy 0.74 0.68 0.71 1.00 0.76 0.74 0.72 0.64 0.35 0.55 -0.04 0.15 0.18 0.25 0.08 -0.36 -0.37 -0.01 -0.08 -0.19 0.01 0.16 0.10 -0.39 -0.25 -0.22 -0.08 -0.21 0.05 -0.31 -0.30 -0.21 -0.23 -0.40 -0.47 -0.45 -0.50
evebitda 0.59 0.71 0.53 0.76 1.00 0.65 0.67 0.66 0.48 0.66 0.04 0.10 0.05 0.14 -0.04 -0.37 -0.32 -0.04 -0.02 0.00 0.22 0.18 0.30 -0.24 -0.03 -0.02 0.14 -0.05 0.16 -0.14 -0.12 -0.09 -0.01 -0.32 -0.39 -0.34 -0.39
op_cy 0.61 0.51 0.61 0.74 0.65 1.00 0.59 0.48 0.32 0.45 -0.07 0.01 0.04 0.09 -0.02 -0.48 -0.27 0.07 0.04 -0.17 0.07 0.20 0.08 -0.20 -0.09 -0.08 0.03 -0.13 0.07 -0.23 -0.20 -0.13 -0.11 -0.38 -0.37 -0.33 -0.40
by_12m_fwd 0.53 0.53 0.59 0.72 0.67 0.59 1.00 0.55 0.47 0.49 -0.03 0.07 0.02 0.00 -0.08 -0.48 -0.32 0.02 0.00 -0.14 0.18 0.23 0.28 -0.26 -0.20 -0.10 0.04 -0.11 0.09 -0.04 -0.05 -0.11 -0.06 -0.27 -0.35 -0.28 -0.39
ey12m_tr 0.59 0.88 0.39 0.64 0.66 0.48 0.55 1.00 0.59 0.83 0.13 0.42 0.33 0.24 -0.05 -0.15 -0.41 0.11 0.01 0.20 0.24 0.13 0.36 -0.19 -0.14 -0.08 0.26 0.37 0.26 -0.04 -0.08 -0.10 0.08 -0.08 -0.33 -0.16 -0.13
dy_12m_fwd 0.47 0.54 0.08 0.35 0.48 0.32 0.47 0.59 1.00 0.65 -0.04 0.24 0.18 0.07 -0.34 -0.40 -0.06 0.34 0.27 0.07 0.54 0.27 0.56 0.21 0.07 0.18 0.48 0.38 0.57 0.14 0.17 0.33 0.42 -0.08 -0.04 0.07 -0.02
ey_12m_fwd 0.55 0.83 0.26 0.55 0.66 0.45 0.49 0.83 0.65 1.00 0.03 0.36 0.32 0.17 -0.10 -0.21 -0.20 0.17 0.12 0.23 0.34 0.08 0.45 -0.05 0.01 0.04 0.37 0.36 0.32 -0.04 -0.01 -0.01 0.18 -0.10 -0.28 -0.15 -0.05
reversion_1m -0.07 0.06 -0.09 -0.04 0.04 -0.07 -0.03 0.13 -0.04 0.03 1.00 0.33 0.19 0.07 -0.04 0.04 0.13 0.06 0.08 0.08 0.02 0.10 0.01 0.03 -0.09 0.01 0.12 0.15 0.02 -0.02 0.07 0.02 0.14 -0.04 0.15 0.20 0.12
reversion_3m 0.27 0.32 0.07 0.15 0.10 0.01 0.07 0.42 0.24 0.36 0.33 1.00 0.72 0.51 0.03 0.11 -0.14 -0.03 -0.03 0.07 -0.13 -0.04 0.00 -0.18 -0.37 -0.24 0.13 0.15 0.23 -0.18 -0.13 -0.01 0.10 0.01 -0.32 -0.08 0.02
reversion_6m 0.31 0.36 0.10 0.18 0.05 0.04 0.02 0.33 0.18 0.32 0.19 0.72 1.00 0.71 0.12 0.17 -0.15 0.04 -0.03 0.09 -0.15 -0.09 -0.08 -0.21 -0.36 -0.30 0.10 0.07 0.25 -0.29 -0.15 -0.09 0.01 -0.05 -0.40 -0.27 -0.15
reversion_12m 0.34 0.29 0.27 0.25 0.14 0.09 0.00 0.24 0.07 0.17 0.07 0.51 0.71 1.00 0.23 0.21 -0.22 -0.12 -0.23 0.01 -0.33 -0.14 -0.27 -0.39 -0.43 -0.34 -0.10 -0.12 0.05 -0.37 -0.35 -0.24 -0.15 -0.24 -0.59 -0.50 -0.40
debtasset 0.08 0.06 0.16 0.08 -0.04 -0.02 -0.08 -0.05 -0.34 -0.10 -0.04 0.03 0.12 0.23 1.00 0.45 -0.13 -0.36 -0.33 -0.06 -0.54 -0.28 -0.43 -0.30 -0.27 -0.25 -0.51 -0.37 -0.32 -0.37 -0.45 -0.59 -0.54 -0.07 -0.27 -0.31 -0.25
highvol -0.26 -0.08 -0.29 -0.36 -0.37 -0.48 -0.48 -0.15 -0.40 -0.21 0.04 0.11 0.17 0.21 0.45 1.00 0.07 -0.24 -0.19 0.32 -0.43 -0.41 -0.35 -0.07 -0.05 -0.01 -0.24 0.01 -0.22 -0.16 -0.22 -0.47 -0.22 0.28 0.05 0.05 0.16
eps_growth -0.37 -0.32 -0.43 -0.37 -0.32 -0.27 -0.32 -0.41 -0.06 -0.20 0.13 -0.14 -0.15 -0.22 -0.13 0.07 1.00 0.20 0.38 0.04 0.11 -0.07 -0.01 0.44 0.35 0.35 0.11 0.07 0.10 0.10 0.20 0.18 0.28 -0.01 0.47 0.39 0.34
cps_growth 0.10 0.13 -0.18 -0.01 -0.04 0.07 0.02 0.11 0.34 0.17 0.06 -0.03 0.04 -0.12 -0.36 -0.24 0.20 1.00 0.38 0.02 0.42 0.18 0.35 0.40 0.21 0.27 0.45 0.45 0.36 0.06 0.23 0.36 0.43 0.07 0.37 0.43 0.39
dps_growth -0.03 -0.02 -0.35 -0.08 -0.02 0.04 0.00 0.01 0.27 0.12 0.08 -0.03 -0.03 -0.23 -0.33 -0.19 0.38 0.38 1.00 0.18 0.52 0.10 0.49 0.35 0.37 0.29 0.43 0.34 0.30 0.23 0.27 0.32 0.46 0.07 0.34 0.32 0.23
trailing_eps_growth_5y-0.08 0.13 -0.40 -0.19 0.00 -0.17 -0.14 0.20 0.07 0.23 0.08 0.07 0.09 0.01 -0.06 0.32 0.04 0.02 0.18 1.00 0.26 -0.18 0.35 0.09 0.25 0.16 0.41 0.57 0.07 0.34 0.26 0.04 0.32 0.29 0.03 0.09 0.26
upgrades_3m 0.00 0.18 -0.29 0.01 0.22 0.07 0.18 0.24 0.54 0.34 0.02 -0.13 -0.15 -0.33 -0.54 -0.43 0.11 0.42 0.52 0.26 1.00 0.29 0.87 0.46 0.56 0.45 0.65 0.54 0.45 0.45 0.43 0.56 0.61 0.10 0.32 0.31 0.28
upgrades_1m 0.22 0.09 0.21 0.16 0.18 0.20 0.23 0.13 0.27 0.08 0.10 -0.04 -0.09 -0.14 -0.28 -0.41 -0.07 0.18 0.10 -0.18 0.29 1.00 0.22 0.13 0.02 0.28 0.12 -0.03 0.18 -0.08 -0.03 0.15 0.14 -0.01 0.16 0.01 -0.16
upgrades_6m 0.08 0.28 -0.22 0.10 0.30 0.08 0.28 0.36 0.56 0.45 0.01 0.00 -0.08 -0.27 -0.43 -0.35 -0.01 0.35 0.49 0.35 0.87 0.22 1.00 0.35 0.49 0.33 0.62 0.55 0.40 0.43 0.31 0.44 0.55 0.19 0.16 0.23 0.24
rev6 -0.31 -0.21 -0.45 -0.39 -0.24 -0.20 -0.26 -0.19 0.21 -0.05 0.03 -0.18 -0.21 -0.39 -0.30 -0.07 0.44 0.40 0.35 0.09 0.46 0.13 0.35 1.00 0.67 0.59 0.28 0.39 0.29 0.33 0.33 0.36 0.32 0.33 0.51 0.52 0.50
rev3 -0.31 -0.11 -0.44 -0.25 -0.03 -0.09 -0.20 -0.14 0.07 0.01 -0.09 -0.37 -0.36 -0.43 -0.27 -0.05 0.35 0.21 0.37 0.25 0.56 0.02 0.49 0.67 1.00 0.65 0.32 0.37 0.21 0.40 0.25 0.28 0.30 0.24 0.36 0.31 0.38
rev1 -0.16 -0.04 -0.31 -0.22 -0.02 -0.08 -0.10 -0.08 0.18 0.04 0.01 -0.24 -0.30 -0.34 -0.25 -0.01 0.35 0.27 0.29 0.16 0.45 0.28 0.33 0.59 0.65 1.00 0.30 0.30 0.20 0.25 0.25 0.22 0.33 0.24 0.40 0.34 0.36
rnoa -0.02 0.22 -0.43 -0.08 0.14 0.03 0.04 0.26 0.48 0.37 0.12 0.13 0.10 -0.10 -0.51 -0.24 0.11 0.45 0.43 0.41 0.65 0.12 0.62 0.28 0.32 0.30 1.00 0.71 0.43 0.34 0.47 0.58 0.78 0.13 0.16 0.27 0.35
roe -0.10 0.24 -0.43 -0.21 -0.05 -0.13 -0.11 0.37 0.38 0.36 0.15 0.15 0.07 -0.12 -0.37 0.01 0.07 0.45 0.34 0.57 0.54 -0.03 0.55 0.39 0.37 0.30 0.71 1.00 0.26 0.46 0.43 0.37 0.60 0.40 0.25 0.42 0.53
payout 0.10 0.23 -0.21 0.05 0.16 0.07 0.09 0.26 0.57 0.32 0.02 0.23 0.25 0.05 -0.32 -0.22 0.10 0.36 0.30 0.07 0.45 0.18 0.40 0.29 0.21 0.20 0.43 0.26 1.00 0.15 0.22 0.38 0.31 -0.03 0.14 0.15 0.16
net_margin -0.41 -0.20 -0.39 -0.31 -0.14 -0.23 -0.04 -0.04 0.14 -0.04 -0.02 -0.18 -0.29 -0.37 -0.37 -0.16 0.10 0.06 0.23 0.34 0.45 -0.08 0.43 0.33 0.40 0.25 0.34 0.46 0.15 1.00 0.66 0.36 0.32 0.26 0.26 0.31 0.35
gross_margin -0.32 -0.20 -0.40 -0.30 -0.12 -0.20 -0.05 -0.08 0.17 -0.01 0.07 -0.13 -0.15 -0.35 -0.45 -0.22 0.20 0.23 0.27 0.26 0.43 -0.03 0.31 0.33 0.25 0.25 0.47 0.43 0.22 0.66 1.00 0.46 0.50 0.23 0.31 0.35 0.42
merton -0.18 -0.19 -0.45 -0.21 -0.09 -0.13 -0.11 -0.10 0.33 -0.01 0.02 -0.01 -0.09 -0.24 -0.59 -0.47 0.18 0.36 0.32 0.04 0.56 0.15 0.44 0.36 0.28 0.22 0.58 0.37 0.38 0.36 0.46 1.00 0.68 0.03 0.30 0.31 0.35
ebitint -0.11 0.02 -0.49 -0.23 -0.01 -0.11 -0.06 0.08 0.42 0.18 0.14 0.10 0.01 -0.15 -0.54 -0.22 0.28 0.43 0.46 0.32 0.61 0.14 0.55 0.32 0.30 0.33 0.78 0.60 0.31 0.32 0.50 0.68 1.00 0.09 0.32 0.37 0.40
change_in_roe -0.23 -0.13 -0.27 -0.40 -0.32 -0.38 -0.27 -0.08 -0.08 -0.10 -0.04 0.01 -0.05 -0.24 -0.07 0.28 -0.01 0.07 0.07 0.29 0.10 -0.01 0.19 0.33 0.24 0.24 0.13 0.40 -0.03 0.26 0.23 0.03 0.09 1.00 0.33 0.41 0.40
momentum_12x1m -0.42 -0.34 -0.45 -0.47 -0.39 -0.37 -0.35 -0.33 -0.04 -0.28 0.15 -0.32 -0.40 -0.59 -0.27 0.05 0.47 0.37 0.34 0.03 0.32 0.16 0.16 0.51 0.36 0.40 0.16 0.25 0.14 0.26 0.31 0.30 0.32 0.33 1.00 0.83 0.60
momentum_12x3m -0.37 -0.23 -0.45 -0.45 -0.34 -0.33 -0.28 -0.16 0.07 -0.15 0.20 -0.08 -0.27 -0.50 -0.31 0.05 0.39 0.43 0.32 0.09 0.31 0.01 0.23 0.52 0.31 0.34 0.27 0.42 0.15 0.31 0.35 0.31 0.37 0.41 0.83 1.00 0.74
momentum_24x3m -0.43 -0.23 -0.58 -0.50 -0.39 -0.40 -0.39 -0.13 -0.02 -0.05 0.12 0.02 -0.15 -0.40 -0.25 0.16 0.34 0.39 0.23 0.26 0.28 -0.16 0.24 0.50 0.38 0.36 0.35 0.53 0.16 0.35 0.42 0.35 0.40 0.40 0.60 0.74 1.00
8
Cluster Analysis
9
Relative performance of the Best Styles investment factors Value, Revisions , Momentum, Quality, Growth, Low Risk, Mean Reversion and Small Cap Beta
Source: Allianz Global Investors, as at 31/03/2016. Past performance is not a reliable indicator of future results.
-2%
0%
2%
4%
6%
8%
10%
12%
Value Revisions Momentum Quality Growth Low Risk MeanReversion
Small Cap
10
Relative performance of Value factors Value measures on earnings and dividend outperform those based on book value
Source: Allianz Global Investors, as at 31/12/2016. Past performance is not a reliable indicator of future results. Calculated as using equal weighted quintile portfolios of investment factors
vs. an equal weighted benchmark. Data since 30/11/2004. Unlike actual performance data, simulations are not based on actual transactions; thus, their significance underlies inherent
limitations. Simulations are not able to account for the impact of actual portfolio trading as it may have been affected by economic and market factors, such as a lack of liquidity.
0.7
0.9
1.1
1.3
1.5
1.7
1.9
Dividend Yield
Cash Yield
Earnings Yield
Book Yield
Op. Cash Yield
Ebitda to EV
11
Relative performance of Revisions factors Revisions works better over a longer time frame in China: 3M and 6M revisions
outperform 1M revisions
Source: Allianz Global Investors, as at 31/12/2016. Past performance is not a reliable indicator of future results. Calculated as using equal weighted quintile portfolios of investment factors
vs. an equal weighted benchmark. Data since 30/11/2004. Unlike actual performance data, simulations are not based on actual transactions; thus, their significance underlies inherent
limitations. Simulations are not able to account for the impact of actual portfolio trading as it may have been affected by economic and market factors, such as a lack of liquidity.
0.7
0.8
0.9
1
1.1
1.2
1.3
1.4
1.5
1.6
1.7
3M EPS Revisions
6M EPS Revisions
Upgrades / Downgrades ratio 3M
1M EPS Revisions
Upgrades / Downgrades ratio 6M
12
Relative performance of Momentum factors Momentum is weak across the board in China on most measures
Typical definitions of momentum underperform
Source: Allianz Global Investors, as at 31/12/2016. Past performance is not a reliable indicator of future results. Calculated as using equal weighted quintile portfolios of investment factors
vs. an equal weighted benchmark. Data since 30/11/2004. Unlike actual performance data, simulations are not based on actual transactions; thus, their significance underlies inherent
limitations. Simulations are not able to account for the impact of actual portfolio trading as it may have been affected by economic and market factors, such as a lack of liquidity.
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
12x3M Price Momentum
12x1M Price Momentum
24x1M Price Momentum
6M Price Momentum
3M Price Momentum
13
Momentum strategies do not work over any horizon in China,
unlike in the developed world
Source: Allianz Global Investors, as at 31/12/2016. Past performance is not a reliable indicator of future results. Calculated as using equal weighted quintile portfolios of investment factors
vs. an equal weighted benchmark. Data since 30/11/2004. Unlike actual performance data, simulations are not based on actual transactions; thus, their significance underlies inherent
limitations. Simulations are not able to account for the impact of actual portfolio trading as it may have been affected by economic and market factors, such as a lack of liquidity.
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
1M
Mo
me
ntu
m
2M
Mo
me
ntu
m
3M
Mo
me
ntu
m
4M
Mo
me
ntu
m
5M
Mo
me
ntu
m
6M
Mo
me
ntu
m
7M
Mo
me
ntu
m
8M
Mo
me
ntu
m
9M
Mo
me
ntu
m
10
M M
om
en
tum
11
M M
om
en
tum
12
M M
om
en
tum
13
M M
om
en
tum
14
M M
om
en
tum
15
M M
om
en
tum
18
M M
om
en
tum
24
M M
om
en
tum
36
M M
om
en
tum
Information Ratio of Momentum strategies
Developed World
China
14
Relative performance of Mean Reversion factors Mean Reversion is very strong in China on all horizons
Mean Reversion performs strongly even when rebalanced at lower frequencies
Source: Allianz Global Investors, as at 31/12/2016. Past performance is not a reliable indicator of future results. Calculated as using equal weighted quintile portfolios of investment factors
vs. an equal weighted benchmark. Data since 30/11/2004. Unlike actual performance data, simulations are not based on actual transactions; thus, their significance underlies inherent
limitations. Simulations are not able to account for the impact of actual portfolio trading as it may have been affected by economic and market factors, such as a lack of liquidity.
0.5
0.7
0.9
1.1
1.3
1.5
1.7
1.9
3M Mean reversion
12M Mean Reversion
1M Mean Reversion
6M Mean Reversion
15
Relative performance of Growth factors Backward looking growth measures are weak overall
Source: Allianz Global Investors, as at 31/12/2016. Past performance is not a reliable indicator of future results. Calculated as using equal weighted quintile portfolios of investment factors
vs. an equal weighted benchmark. Data since 30/11/2004. Unlike actual performance data, simulations are not based on actual transactions; thus, their significance underlies inherent
limitations. Simulations are not able to account for the impact of actual portfolio trading as it may have been affected by economic and market factors, such as a lack of liquidity.
0.5
0.6
0.7
0.8
0.9
1
1.1
1.2
1.3
1.4
1.5
Trailing 1Y Sales Growth
Trailing 3Y Sales Growth
Trailing 3Y EPS Growth
Trailing 1Y EPS Growth
Trailing 12M Net Margin Growth
16
Relative performance of Quality factors Low Vol shows better performance than other quality measures
Source: Allianz Global Investors, as at 31/12/2016. Past performance is not a reliable indicator of future results. Calculated as using equal weighted quintile portfolios of investment factors
vs. an equal weighted benchmark. Data since 30/11/2004. Unlike actual performance data, simulations are not based on actual transactions; thus, their significance underlies inherent
limitations. Simulations are not able to account for the impact of actual portfolio trading as it may have been affected by economic and market factors, such as a lack of liquidity.
0.5
0.7
0.9
1.1
1.3
1.5
1.7
1.9
2.1
RNoA
RoE
Merton Distance to Default
Net Margin
Debt/Assets
Low Vol
17
Performance of key investment styles in
China vs. Emerging Markets vs. Developed Markets Momentum is the clear outlier in the China A-share market compared with
Emerging Markets and Developed Markets
Source: Allianz Global Investors, as at 31/12/2016. Past performance is not a reliable indicator of future results. Calculated as using equal weighted quintile portfolios of investment styles vs.
an equal weighted benchmark, implemented on a sector neutral basis. Data since 30/11/2004. Unlike actual performance data, simulations are not based on actual transactions; thus, their
significance underlies inherent limitations. Simulations are not able to account for the impact of actual portfolio trading as it may have been affected by economic and market factors, such as
a lack of liquidity.
-2%
0%
2%
4%
6%
8%
10%
12%
14%
Value Revisions Momentum Quality Growth Low Risk Size
Relative Return
China
EM
DM
Information Ratio Rebalancing Period
1m 2m 3m 6m 9m 12m
Value 0.67 0.54 0.38 0.35 0.11 0.07
Revisions 1.07 0.80 0.66 0.50 0.48 0.27
Momentum -0.03 -0.22 -0.24 -0.38 -0.49 -0.42
Quality 0.23 0.14 0.15 0.06 0.03 0.03
Growth 0.47 0.48 0.40 0.23 0.23 0.27
Low Risk 0.65 0.59 0.49 0.27 0.26 0.22
Mean Reversion 0.90 0.60 0.49 0.35 0.32 0.19
Impact of rebalancing frequency on Investment Style performance Most investment style performance decays sharply at rebalancing frequencies longer than 6m.
Rebalancing every 3-6 months can be a good strategy after costs
Source: Allianz Global Investors, as at 31/12/2016. Past performance is not a reliable indicator of future results. Calculated as using equal weighted quintile portfolios of investment styles vs. an equal
weighted benchmark, implemented on a sector neutral basis. Data since 30/11/2004. Unlike actual performance data, simulations are not based on actual transactions; thus, their significance underlies
inherent limitations. Simulations are not able to account for the impact of actual portfolio trading as it may have been affected by economic and market factors, such as a lack of liquidity.
Relative Return p.a. Rebalancing Period
1m 2m 3m 6m 9m 12m
Value 5.2% 4.3% 2.9% 2.7% 0.8% 0.5%
Revisions 8.5% 6.4% 5.1% 3.7% 4.4% 2.5%
Momentum -0.3% -1.9% 0.5% -3.2% -4.3% -3.6%
Quality 1.8% 1.1% 1.3% 0.5% 0.1% 0.3%
Growth 3.1% 3.1% 2.6% 1.5% 2.3% 2.9%
Low Risk 6.9% 6.1% 5.1% 2.7% 2.3% 2.0%
Mean Reversion 7.9% 5.3% 4.3% 2.8% 3.4% 1.9%
19
Dec 2004 – Oct 2016: Historic simulation: Monthly rebalancing, performance before transaction costs.
Unlike actual performance data, simulations are not based on actual transactions; thus, their significance underlies inherent limitations. Simulations are not able to account for the impact of actual portfolio trading as it may have been
affected by economic and market factors, such as a lack of liquidity.
Investment styles can have prolonged periods of lackluster performance
Successful style investing needs to address the short-term volatility of investment styles
Relative performance of investment styles for a China universe
-40%
-20%
0%
20%
40%
60%
80%
100%
120%
140%
160%
180%
04 06 08 10 12 14
Valuation Revisions
20
The outperformance path of a diversified investment style mix of Value and Revisions is much more stable
Dec 2004 – Oct 2016: Historic simulation: Monthly rebalancing, performance before transaction costs.
Unlike actual performance data, simulations are not based on actual transactions; thus, their significance underlies inherent limitations. Simulations are not able to account for the impact of actual portfolio trading as it may have been
affected by economic and market factors, such as a lack of liquidity.
Relative performance of investment styles for a China universe
Investment style diversification is key to stable outperformance
Investment style diversification: marrying attractive performance to high performance stability
-40%
0%
40%
80%
120%
160%
04 06 08 10 12 14
Valuation Revisions Diversified Style Mix
Improving performance
through combination of Value and Revisions
Information Ratio 1 month rebalancing 3 month rebalancing 6 month rebalancing
Value 0.67 0.38 0.35
Revisions 1.07 0.66 0.50
Best Styles Combination 1.35 0.73 0.60
Separately, Value and Revisions are both risks that are priced in the China A-share market.
However, both these styles suffer from periods of prolonged underperformance
A combination of these two negatively correlated styles can result in a much more stable performance
Using long term correlation structure, Best Styles strategies target style allocations that can outperform over the entire
business cycle
Dec 2004 – Dec 2016: Historic simulation: performance before transaction costs.
Unlike actual performance data, simulations are not based on actual transactions; thus, their significance underlies inherent limitations. Simulations are not able to account for the impact of actual portfolio
trading as it may have been affected by economic and market factors, such as a lack of liquidity.
Blend of smart beta factors
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
1.2
1.4b
eta
GD
P
10
yrs
inte
rest
rat
es FX Oil
Co
nsu
me
rC
on
fid
ence
Mfg
PM
I
Serv
ices
PM
I
Ener
gy
Fin
anci
als
Shan
ghai
She
nzh
en
US
Stan
dar
diz
ed
exp
osu
re
Combination of rewarding investment styles – still not sufficient Unmanaged exposure to non rewarding risks can threaten outperformance
Investors risk piling on to overcrowded macro exposures or trades
Target range
un-managed risks
Establishing an exposure to the rewarding risks of investment styles means loading up also unrewarding risk factors,
such as interest rates risk, oil price risks, sector risks, policy risks, etc.
Portfolio with diversified exposures to investment styles but unmitigated exposures to non-rewarding risks
For illustrative purposes only
Source: Allianz Global Investors, Bloomberg
Summary
China has the potential to be to Emerging Markets what the US is presently to the global developed
equity markets
The depth and breadth of stocks in China provides a good testing ground for factor investors to test
their strategies
Many traditional investment styles can be harvested for risk premia in Chinese A-shares similar to the
experience in Developed Markets
China also opens up the opportunity to explore new factors like mean reversion as a means of
delivering excess returns
Diversification is the key to better risk-adjusted performance. Factors can be combined in various
ways to improve risk adjusted performance
Risk management is as important as ever for achieving stable outperformance over the long term
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