“Market Insights Through the Lens of a Risk Model” by Olivier d'Assier, Head of Applied Research, APAC for Axioma

The Current Risk Landscape:
Axioma Insight Findings
QuantCon Singapore 2017
Olivier d’Assier
Managing Director, Applied Research APAC
Axioma Inc.
August 2017

3QuantCon Singapore 2017 – Copyright © 2017 Axioma
Major Benchmark Risk and Return: Risk estimates have ticked up slightly in many cases
Market Risk
Source: FTSE Russell, Axioma
-8%
-4%
0%
4%
8%
12%
16%
6%
8%
10%
12%
14%
Aug Oct Dec Feb Apr Jun Aug
Russell 1000
-8%
-4%
0%
4%
8%
12%
16%
20%
8%
10%
12%
14%
16%
18%
Russell 2000
-4%
0%
4%
8%
12%
7%
8%
9%
10%
11%
12%
TSX Composite
-4%
0%
4%
8%
12%
16%
20%
24%
8%
10%
12%
14%
16%
18%
20%
22%
24%
26%
FTSE Japan
-4%
0%
4%
8%
12%
16%
8%
10%
12%
14%
16%
18%
20%
FTSE 350
-8%
-4%
0%
4%
8%
12%
16%
20%
8%
10%
12%
14%
16%
18%
20%
22%
FTSE Dev Europe
-8%
-4%
0%
4%
8%
12%
16%
20%
6%
8%
10%
12%
14%
16%
FTSE Developed
-8%
-4%
0%
4%
8%
12%
16%
20%
24%
8%
10%
12%
14%
16%
18%
20%
FTSE Emerging

4
Market Risk
APxJP and Emerging
Markets saw risk increase
since June, driven by
higher risk in China
A year ago Japan was the
riskiest of the major
markets; it is now closer to
the low end
*FTSE Europe minus FTSE Eurobloc
**Portugal, Italy, Ireland, Greece and Spain from FTSE Eurobloc
Source: FTSE Russell, Standard & Poor's, China Securities Index Company, Ltd, Axioma Inc.
0
5
10
15
20
25
Russell1000
Russell2000
TSXComposite
FTSE350
FTSEEurobloc
FTSEEurope
Non-Eurobloc*
EuroCrisis**
FTSEAsiaPacific
FTSEAsiaPacificex-
Japan
SP-ASX200
ChinaCSI300
FTSEJapan
FTSEDeveloped
FTSEEmerging
FTSE-AllWorld
North America Europe Asia-Pacific Global
Short-Horizon Predicted Volatility
30-Sep-16 30-Dec-16 31-Mar-17 30-Jun-17 31-Aug-17

5Confidential – Not for Redistribution – Copyright © 2017 Axioma
Market Risk
Both developed and emerging markets risk levels are near 17 year lows
Short-Horizon Fundamental Risk
0%
10%
20%
30%
40%
50%
60%
FTSE Developed
0%
10%
20%
30%
40%
50%
60%
70%
80%
2000 2002 2004 2006 2008 2010 2012 2014 2016
FTSE Emerging
• DM SH risk bottomed in early August and is up about
1% from that point
• EM SH risk bottomed in 2014 but also remains low
• EM/DM hit a recent low in early July and has climbed
since then
0.50
0.70
0.90
1.10
1.30
1.50
1.70
1.90
Jan-16 Mar-16 May-16 Jul-16 Sep-16 Nov-16 Jan-17 Mar-17 May-17 Jul-17
Emerging/Developed

Market Risk
The Russell 1000 hit a 35-year low of just above 6% on August 9, 2017 and is now about 1.3% higher
Short-Horizon Fundamental Risk
0%
10%
20%
30%
40%
50%
60%
1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016

Country and Currency Risk
All three major components of risk have ticked back
up since the mid-August low. Increases in currency
and country risk are slight.
Major Components of Short-Horizon Risk: FTSE Global Developed Index (USD base)
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
3.5%
5.0%
7.0%
9.0%
11.0%
13.0%
15.0%
17.0%
19.0%
21.0%
Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug
Short Horizon
Market-SH (Left Scale)
Country-SH (Right Scale)
Currency-SH (Right Scale)

Risk of individual currencies has
declined steadily throughout the
last 12 months. Only CHF saw
an increase during Q3
Source: Axioma
Developed Market Currency Volatility (vs. USD)
0.0%
2.0%
4.0%
6.0%
8.0%
10.0%
12.0%
14.0%
JPY NZD GBP SEK NOK AUD CHF EUR DKK CAD SGD
9/30/2016 3/31/2017 6/30/2017 8/31/2017

10
Currency Correlations had a recent peak in
August 2016, but have fallen since then, so even
with similar levels of volatility, currency
movements are less aligned with each other
The biggest correlation increase was between
GBP and JPY, the biggest decrease between
CHF and SEK
Source: Axioma
-0.2
-0.1
0.0
0.1
0.2
0.3
0.4
0.5
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Worldwide Model Median Factor Correlations
Style Country Industry Currency

Increased geopolitical
risk has not seemed to
show up in equity
markets
Switzerland’s risk
relative to other
countries has been
edging up all year
Source: Axioma
Developed Countries Extra-Market Risk Levels
0%
2%
4%
6%
8%
10%
12%
14%
16%
9/30/2016 3/31/2017 6/30/2017 8/31/2017

EM currency risk has continued to fall but market
risk has gone up
Major Components of Short-Horizon Risk: FTSE Emerging Index (USD base)
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
7.0%
6.0%
7.0%
8.0%
9.0%
10.0%
11.0%
12.0%
13.0%
14.0%
Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug
Short Horizon
Market-SH (Left)
Country-SH (Right)
Currency-SH (Right)

Only CNY has higher
volatility since the end of
June, but the level remains
quite low
Even KRW continues to see
its volatility drop
Source: Axioma
Emerging Market Currency Volatility (vs. USD)
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
ZAR BRL MXN RUB TRY KRW INR THB TWD CNY IDR
9/30/2016 3/31/2017 6/30/2017 8/31/2017

South Korea’s equity
risk has fallen as well
as its currency risk
Most other countries
have seen risk fall as
well
Source: Axioma
Emerging Countries Extra-Market Risk Levels
0%
4%
8%
12%
16%
20%
9/30/2016 3/31/2017 6/30/2017 8/31/2017

15
Correlations and Dispersion

Renewed geopolitical concerns have not driven correlations back up
Correlations and Dispersion
Source: FTSE Russell, Standard and Poor’s, Axioma
0
0.1
0.2
0.3
0.4
0.5
0.6
Jan-15
Apr-15
Jul-15
Oct-15
Jan-16
Apr-16
Jul-16
Oct-16
Jan-17
Apr-17
Jul-17
Russell 1000 Russell 2000
0
0.1
0.2
0.3
0.4
0.5
0.6
Jan-15
Apr-15
Jul-15
Oct-15
Jan-16
Apr-16
Jul-16
Oct-16
Jan-17
Apr-17
Jul-17
TSX FTSE 350
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Jan-15
Apr-15
Jul-15
Oct-15
Jan-16
Apr-16
Jul-16
Oct-16
Jan-17
Apr-17
Jul-17
FTSE Dev Europe FTSE APxJP
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Jan-15
Apr-15
Jul-15
Oct-15
Jan-16
Apr-16
Jul-16
Oct-16
Jan-17
Apr-17
Jul-17
FTSE Japan ASX 200
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
Jan-15
Apr-15
Jul-15
Oct-15
Jan-16
Apr-16
Jul-16
Oct-16
Jan-17
Apr-17
Jul-17
FTSE Developed FTSE Emerging

Average monthly asset-return dispersion
Correlation and Dispersion
Dispersion is the cross-sectional standard deviation
of monthly returns for stocks included in each
benchmark
Asset dispersion has increased in many markets,
even with volatility so low
Low correlations, high dispersion and high specific
risk are all theoretically good indicators for stock
pickers, as the reward to picking the right stocks is
higher
Source: FTSE Russell, Axioma.
0%
2%
4%
6%
8%
10%
12%
14%
Russell
1000
Russell
2000
FTSE 350 FTSE
Developed
Europe
FTSE Asia
Pacific
FTSE Japan CSI 300 ASX 200 FTSE
Developed
FTSE
Emerging
Average Monthly Asset Dispersion
Long-Term Q4 2016 Q1 2017 Q2 2017 Q3 2017

18
Style Factor and Sample
Portfolio Performance

Style Factor Performance
Momentum Has Been Quite Strong So Far in Q3
Source: Axioma
US Canada UK Europe
Asia Pac ex-
Japan Japan Australia Worldwide
Emerging
Markets
July-August Return (Highest and Lowest region for each factor is highlighted)
Momentum 2.23% 1.78% 2.19% 2.06% 2.50% 1.52% 0.46% 2.43% 2.61%
Value 0.62% 0.77% -0.05% 0.80% 0.65% 0.84% -0.91% 0.56% 0.76%
Volatility -1.12% -2.59% 0.03% 0.83% -0.25% -0.15% 1.32% -0.30% 0.72%
Growth 0.42% 0.06% 0.61% 0.38% 0.34% 0.27% -0.39% 0.32% 0.10%
Exch Rate Sens -0.74% — -0.31% -0.09% 0.32% 0.49% 2.45% -0.07% 0.40%
Size 1.77% -0.14% 1.49% 0.93% 2.99% -1.61% -1.94% 1.78% 3.00%
Leverage 0.20% 1.27% 0.80% 0.36% -0.14% -0.34% -0.12% -0.04% -0.12%
Liquidity -0.16% 0.90% -0.16% 0.05% 0.94% -0.30% 0.19% -0.09% 0.93%
Dividend Yield -0.86% — — — — 0.32% 0.70% — —
Profitability 0.38% — — — — 0.38% 2.58% — —
Earnings Yield 0.33% — — — — 0.51% — — —
July-August Risk Adjusted Return
Momentum 2.17 1.17 2.51 2.10 4.69 1.12 0.27 3.33 5.25
Value 1.03 0.87 -0.08 1.16 1.00 1.05 -0.74 1.14 1.29
Volatility -0.74 -1.26 0.04 0.59 -0.24 -0.13 0.51 -0.25 0.75
Growth 0.81 0.09 1.22 0.69 0.78 0.49 -0.31 0.96 0.24
Exch Rate Sens -1.40 — -0.18 -0.14 0.91 0.68 1.91 -0.17 1.17
Size 0.84 -0.12 1.03 0.50 1.65 -0.91 -0.85 1.52 1.68
Leverage 0.45 1.91 1.33 1.02 -0.39 -0.64 -0.13 -0.16 -0.36
Liquidity -0.25 1.02 -0.25 0.08 1.16 -0.33 0.15 -0.18 1.24
Dividend Yield -0.74 — — — — 0.49 2.45 — —
Profitability 0.61 — — — — 0.63 2.25 — —
Earnings Yield 0.41 — — — — 0.87 — — —

Momentum Really Stands Out in APxJP
Source: Axioma
US Canada UK Europe
Asia Pac ex-
Japan Japan Australia Worldwide
Emerging
Markets
YTD Return (Highest and Lowest region for each factor is highlighted)
Momentum 3.89% 4.48% 4.37% 4.17% 7.06% 3.26% 3.15% 5.05% 5.99%
Value 1.17% -1.04% -1.48% 1.69% 4.15% -0.74% 0.50% 1.98% 4.07%
Volatility -3.91% -10.09% -2.89% -2.56% -6.71% 0.59% -5.22% -5.10% -4.33%
Growth -0.57% -0.54% 2.01% -3.00% 2.41% -2.05% -4.09% -0.25% 0.68%
Exch Rate Sens 0.43% — -1.60% -0.27% 1.66% 1.33% 0.13% -0.36% 2.03%
Size 5.30% -0.31% 1.88% -3.78% 8.15% -5.71% -4.21% 2.45% 6.09%
Leverage -0.24% 1.46% 0.45% 0.05% 1.41% -0.74% -0.61% 0.16% 1.10%
Liquidity 0.73% -1.63% 0.98% 0.68% 1.11% 0.12% -1.77% 0.13% 1.08%
Dividend Yield -1.24% — — — — 1.43% -0.85% — —
Profitability 0.20% — — — — 0.56% 4.78% — —
Earnings Yield 0.14% — — — — 0.55% — — —
YTD Risk Adjusted Return
Momentum 1.34 1.22 2.13 1.66 4.83 0.95 0.81 2.37 4.31
Value 0.66 -0.48 -0.93 1.04 2.54 -0.38 0.17 1.58 2.75
Volatility -0.94 -2.12 -1.31 -0.54 -2.15 0.20 -0.87 -1.28 -1.52
Growth -0.47 -0.28 1.71 -2.09 2.70 -1.73 -1.55 -0.32 0.72
Exch Rate Sens 0.33 — -0.32 -0.22 1.96 0.86 0.05 -0.42 2.52
Size 1.08 -0.11 0.48 -0.68 1.87 -1.09 -0.78 0.74 1.41
Leverage -0.22 0.86 0.35 0.06 1.87 -0.56 -0.33 0.26 1.52
Liquidity 0.48 -0.72 0.65 0.40 0.58 0.05 -0.63 0.11 0.60
Dividend Yield -1.01 — — — — 1.37 -0.42 — —
Profitability 0.12 — — — — 0.43 1.82 — —
Earnings Yield 0.06 — — — — 0.37 — — —

Returns have been consistent, and Momentum portfolios have fared well
-1.5
-0.5
0.5
1.5
2.5
3.5
4.5
5.5
6.5
7.5
US AU CA GB JP
-1.5
-0.5
0.5
1.5
2.5
3.5
4.5
5.5
6.5
7.5
AP EM EU WW
Momentum Returns / Active Portfolio Returns

Value-based factors have had mixed results...
-3
-2
-1
0
1
2
3
4
5 Value
US AU CA GB JP
-3
-1
1
3
5 Value
AP EM EU WW
-1.1
-0.6
-0.1
0.4
0.9 Earnings Yield
US JP

In portfolios, Low Volatility did well
Volatility Returns
-11
-9
-7
-5
-3
-1
1
3
US AU CA
GB JP -11
-9
-7
-5
-3
-1
1
3
AP EM EU WW

Growth did well in several regions
Growth Returns
-1
-0.5
0
0.5
1
1.5
2
2.5
3 Growth
US AU CA GB JP
-1
-0.5
0
0.5
1
1.5
2
2.5
3
AP EM EU WW

Profitability has done very well in Australia since Q2
Profitability Returns
-1
0
1
2
3
4
5
US AU JP

Multi-Asset Class Risk Review
26

27
Overview
Confidential - Copyright © 2017 Axioma
• Multi-asset class risk review
• Government bond yields driven by (geo-)political risk, as focus temporarily shifts away from economy and central banks
• Euro rises to highest level for almost 3 years on the back of dollar weakness, strong economic performance and
prospect of tighter monetary policy
• Pound recovers after reaching 8-year low versus euro despite sluggish Brexit negotiations
• Swiss franc and Japanese yen dominated by safe-haven buying
• Portfolio risk
• Multi-asset class risk factor correlations over time
• Negative correlation between equity and FX
• Positive correlation between equity and FX
• Positive correlation between stocks and bonds
• Current portfolio risk

28
Government Yields
Government bond yields driven by geopolitical risk
as focus shifted away from economy, European politics and central banks
Geopolitical tensions
Focus on conflict with North Korea and White
House politics
European political risk
Investors relaxed about upcoming German
vote after relief of French election
European Central Bank
Markets await further signals on bond-
purchase tapering
UK Gilts
BoE faces dilemma of high inflation and
economic uncertainty, while Brexit talks stall
French
election
Geopolitical
tensions
Trump impeachment?
ECB
conference
Tory lead
shrinks
UK
election ECB
conference
UK election
announced
BoE turmoil
BoE backpedals

29
EUR / USD Exchange Rate and Risk
Euro rises to highest level for almost 3 years
as focus shifted away from economy, European politics and central banks
Political risk
Rally triggered by relief after French election;
markets relaxed about German vote
Dollar weakness
Based on concerns about White House policy
and geopolitical tensions
Eurozone economy
Shows signs of strong performance
Monetary policy
Prospect of tighter monetary conditions
French
election
Trump
Impeachment?
ECB
conference

31
Currency Risk – Swiss Franc and Japanese Yen
CHF and JPY driven by safe-haven buying
but SNB dampens markets with intervention warning
CHF/USD USD/JPY
French
election
Trump
Impeachment?
ECB
conference
SNB
warns
markets
(Geo-)political
turmoil
Trump
Impeachment?
Geopolitical
tensions

32
Multi-Asset Class Risk Summary
• US Treasury yields driven by geopolitical tensions (North Korea) and concerns about
current administration’s ability to implement policies
• European government bonds rocked by central bank comments
• Euro rose strongly on relief after French election, political uncertainty in the US, strong
economic performance and prospect of tighter monetary policy
• Pound once again driven by Bank of England and Brexit negotiations
• Swiss franc profited from safe-haven buying, but was dampened by SNB concerns
• Yen provides diversification versus USD and EUR due to negative correlation

34
Portfolio Risk Overview
• Multi-asset class risk factor correlations over time
• Major factor correlations change as focus shifts from economy to political risk and inflation concerns subside
• Negative correlation between equity and FX (early March)
• Focus on US economy
• Non-US equity gains offset by FX movements
• Positive correlation between equity and FX (end of April)
• Focus on political events in Europe
• Global equity holdings seemed more correlated, increasing risk contribution
• Positive correlation between stocks and bonds (July)
• Inflation concerns subside, while economic outlook remains strong
• Diversification benefit reduced significantly
• Current portfolio risk
• Dominated by geopolitical concerns (negative correlation of equity with FX and interest rate returns)
• Contribution from gold increased significantly after strong rally

Risk Type FX Equity Inflation
Interest
Rate
Issuer
Credit Vega Comdty
FX 1.00 -0.40 -0.29 0.55 -0.35 -0.51 0.30
Equity -0.40 1.00 0.32 -0.29 0.52 0.39 -0.06
Inflation -0.29 0.32 1.00 -0.28 0.32 0.24 0.06
Interest Rate 0.55 -0.29 -0.28 1.00 -0.65 -0.91 0.35
Issuer Credit -0.35 0.52 0.32 -0.65 1.00 0.59 -0.03
Vega -0.51 0.39 0.24 -0.91 0.59 1.00 -0.35
Commodity 0.30 -0.06 0.06 0.35 -0.03 -0.35 1.00
Interest
Rate
Issuer
Credit Vega Comdty
FX 1.00 0.32 -0.04 0.09 0.50 -0.01 0.56
Equity 0.32 1.00 -0.12 0.34 0.23 -0.13 0.49
Inflation -0.04 -0.12 1.00 -0.48 0.29 0.37 0.28
Interest Rate 0.09 0.34 -0.48 1.00 -0.36 -0.89 -0.05
Issuer Credit 0.50 0.23 0.29 -0.36 1.00 0.46 0.31
Vega -0.01 -0.13 0.37 -0.89 0.46 1.00 0.24
Commodity 0.56 0.49 0.28 -0.05 0.31 0.24 1.00
35
Multi-Asset Class Portfolio Risk Factor Correlations
July 28, 2017 Sep. 1, 2017
March 3, 2017 April 28, 2017
Interest
Rate
Issuer
Credit Vega Comdty
FX 1.00 -0.49 -0.03 0.53 -0.35 -0.34 0.74
Equity -0.49 1.00 -0.01 -0.46 0.58 0.41 -0.16
Inflation -0.03 -0.01 1.00 -0.59 0.03 0.52 -0.25
Interest Rate 0.53 -0.46 -0.59 1.00 -0.60 -0.62 0.64
Issuer Credit -0.35 0.58 0.03 -0.60 1.00 0.35 -0.31
Vega -0.34 0.41 0.52 -0.62 0.35 1.00 -0.45
Commodity 0.74 -0.16 -0.25 0.64 -0.31 -0.45 1.00
Interest
Rate
Issuer
Credit Vega Comdty
FX 1.00 0.04 -0.07 0.39 -0.18 -0.17 0.47
Equity 0.04 1.00 -0.06 -0.17 0.44 0.11 0.15
Inflation -0.07 -0.06 1.00 -0.64 -0.15 0.59 -0.51
Interest Rate 0.39 -0.17 -0.64 1.00 -0.33 -0.77 0.68
Issuer Credit -0.18 0.44 -0.15 -0.33 1.00 0.08 0.19
Vega -0.17 0.11 0.59 -0.77 0.08 1.00 -0.78
Commodity 0.47 0.15 -0.51 0.68 0.19 -0.78 1.00
Interest
Rate
Issuer
Credit Vega Comdty
FX 1.00 0.16 -0.36 -0.10 0.20 -0.11 -0.21
Equity 0.16 1.00 -0.09 -0.73 0.84 0.79 -0.40
Inflation -0.36 -0.09 1.00 0.02 -0.11 0.02 0.33
Interest Rate -0.10 -0.73 0.02 1.00 -0.77 -0.88 0.68
Issuer Credit 0.20 0.84 -0.11 -0.77 1.00 0.77 -0.49
Vega -0.11 0.79 0.02 -0.88 0.77 1.00 -0.50
Commodity -0.21 -0.40 0.33 0.68 -0.49 -0.50 1.00

8.11%
4.02%
-4.09%
36
Current Portfolio Risk (Sep. 1, 2017)
Less negative correlation between stocks and gold
led to fivefold increase of risk contribution from gold future holdings
Asset Class weights and risk contributions Weighted risk contributions by Risk Type

“Market Insights Through the Lens of a Risk Model” by Olivier d'Assier, Head of Applied Research, APAC for Axioma

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