The Current Risk Landscape - web1.amchouston.comweb1.amchouston.com/flexshare/001/CFA/2015 Presentations/CFA_… · The Current Risk Landscape Axioma Insight Findings Q3 and October

The Current Risk Landscape

Axioma Insight Findings Q3 and October 2015 Melissa R. Brown, CFA

What is Risk? VIX is One Measure

© Copyright, Axioma, Inc. 2015. All rights reserved. 2

Average since 1999 Source: Yahoo! Finance, STOXX, Axioma Inc.

0

10

20

30

40

50

60

70

80

90

100

2007 2008 2009 2010 2011 2012 2013 2014 2015

VIX VIX Average VSTOXX VSTOXX Average

1015202530354045

Jan FebMar Apr May Jun Jul Aug Sep Oct Nov

Presenter

Presentation Notes

VIX and VSTOXX seem to have become more volatile, with concerns about Europe reflected more in the VSTOXX index.

What is Risk? Sample of Other Measures


• Value at risk

• Downside risk • Interest rate/credit risk

• Liquidity risk

• Reinvestment risk

• Inflation risk

• “Knowing your companies”?

• …

Axioma’s Risk: We Focus on Quantifiable Risks

Risk (Financial) Expected volatility (of a market, portfolio, etc.) over a predefined investment horizon Risk Management “The process of identification, analysis and either acceptance or mitigation of uncertainty in investment decision-making” Investopedia


Axioma Risk Models

• Axioma’s standard product includes 4 risk models per region – 14 countries/regions/global

• By factor structure – Fundamental: uses predefined set of factors, such as country,

industry, currency, style – Statistical: “lets the data speak”

• By horizon – Short horizon: 1 to 2 month forecast – Medium horizon: 3 to 6 month forecast

• In addition, there is a macroeconomic model for the US • Underlying each model is a set of volatilities and correlations, so we can

“peel the onion” and see what is driving market risk – Major components: Market, Industry, Style, Country, Currency, Stock

Specific • Used to measure total risk and active risk

5 © Copyright, Axioma, Inc. 2015. All rights reserved.

Today’s Discussion


• Style factor returns

• How risk models reacted to August downturn and subsequent volatility

• Comparison of benchmarks

• What drove changes in risk: countries, currencies, etc.

• Small vs. large, emerging vs. developed

• Impact of correlations on risk

• China • Asset class correlations

Source: Axioma Inc.

Factor Performance: Momentum and Value

© Copyright, Axioma, Inc. 2015. All rights reserved.

-4

-2

0

2

4

6

8

10

12

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov

Momentum

US CA EU AP

JP AU WW EM

-6

-4

-2

0

2

4

6


Value

US EU AP JP

AU WW EM CA

Presenter

Presentation Notes

Momentum returns did not stand out

Source: Axioma Inc.

Factor Performance: Volatility and Growth


-16

-14

-12

-10

-8

-6

-4

-2

0

2


Volatility

US EU AP JP

AU WW EM CA

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5


Exchange Rate Sensitivity

US EU AP JP WW EM

Presenter

Presentation Notes

Volatility’s returns were in the direction expected, but better than average in Europe Asia and for the global and emerging markets models, but not so good in the US. Growth stood out as particularly bad in Australia, but showed small but steady gains elsewhere

Benchmark Risk


• How quickly risk models reflected market downturn

• Current risk by region

• Changes over time

• Major drivers

Models Reacted Quickly to Market Drops


-12%

-8%

-4%

0%

4%

8%

8%

12%

16%

20%

24%

Dec-14 Feb-15 Apr-15 Jun-15 Aug-15

Russell 1000

-6%

0%

6%

12%

18%

24%

10%

14%

18%

22%

26%

30%


FTSE Developed Europe -8%

-4%

0%

4%

8%

12%

16%

20%

24%

10%

14%

18%

22%

26%

30%


FTSE Japan

-24%

-16%

-8%

0%

8%

16%

10%

12%

14%

16%

18%

20%

22%

24%


FTSE Asia Pac ex-Japan -8%

-4%

0%

4%

8%

8%

10%

12%

14%

16%

18%

20%

22%


FTSE Developed -24%

-16%

-8%

0%

8%

16%

10%

12%

14%

16%

18%

20%

22%

24%

26%


FTSE Emerging

Source: FTSE, Axioma Inc.

How Does Current Risk Look Relative To History?


0%

10%

20%

30%

40%

50%

60%

2007 2008 2009 2010 2011 2012 2013 2014 2015

FTSE Global Developed Index

US Small Cap Risk Is Lower Than Large Cap


Source: FTSE, Russell Investments, Axioma Inc.

0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

2007 2008 2009 2010 2011 2012 2013 2014 2015

Russell 2000 vs. Russell 1000 Risk

Currency Risk Was Generally Up in Q3, But Has Reversed QTD

13 Source: Axioma, Inc.

Developed Market Currency Volatility (vs. USD)


-15%

-10%

-5%

0%

5%

10%

15%

20%

EUR DKK JPY CHF SGD SEK GBP NZD NOK AUD CAD

Change in Risk

Q4 through 05-Nov-2015

Q3 2015

Q2 2015 0%

2%

4%

6%

8%

10%

12%

14%

NOK NZD EUR DKK CHF SEK AUD JPY CAD GBP SGD

Risk Level 05-Nov-2015

Presenter

Presentation Notes

Risk for many currencies surged at year end last year, meaning it was up for the year, whereas it had been down year to date just a few months ago. Since the end of the year it has continued to go up. The biggest gain was in the Swiss franc, not surprisingly, and I will discuss that later.

Risk Also Rose For Most Countries


Change in Extra-Market Country Volatility: Developed


-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

Q4 through 05-Nov-2015 Q3 2015 Q2 2015

Presenter

Presentation Notes

Developed countries with the biggest increases in risk have changed this year. The biggest increases are dominated by European countries Stop

Australia’s Extra-Market Risk Has Climbed

15 Source: Axioma, Inc. © Copyright, Axioma, Inc. 2015. All rights reserved.

0%

2%

4%

6%

8%

10%

12%

14%

16%Risk Level 05-Nov-2015

0%

50%

Greece

Presenter

Presentation Notes

Developed countries with the biggest increases in risk have changed this year. The biggest increases are dominated by European countries Stop

Yield Curves Have Shifted Down Since June

© Copyright, Axioma, Inc. 2015. All rights reserved. 16 Source: Markit, Axioma, Inc.

0.00%

1.00%

2.00%

3.00%

4.00%

0 10 20 30

US

0.00%

0.50%

1.00%

1.50%

2.00%

2.50%

3.00%

0 10 20 30

Canada

0.00%

0.50%

1.00%

1.50%

2.00%

2.50%

3.00%

0 10 20 30

UK

-0.50%

0.00%

0.50%

1.00%

1.50%

2.00%

0 10 20 30

Germany

-0.50%

0.00%

0.50%

1.00%

1.50%

2.00%

2.50%

0 10 20 30

France

-1.00%

0.00%

1.00%

2.00%

3.00%

4.00%

0 10 20 30

Spain

Risk For Most Currencies Rose in Q3, But None Like CNY (Still the Lowest Level of Risk)

17

Source: Axioma, Inc. © Copyright, Axioma, Inc. 2015. All rights reserved.

Emerging Market Currency Volatility (vs. USD)

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

60%

BRL TWD INR THB MXN ZAR IDR TRY RUB

Change in Risk

Q4 through 05-Nov-2015 Q3 2015 Q2 2015

-50%0%

50%100%

CNY

0%

5%

10%

15%

20%

25%

RUB BRL ZAR TRY MXN IDR THB INR TWD CNY

Risk Level 05-Nov-2015

Presenter

Presentation Notes

Most currencies – except the ruble – have seen risk fall substantially relative to the dollar.

China Has Become the Most Volatile EM Country…



0%

5%

10%

15%

20%

25% Risk Level 05-Nov-2015

Presenter

Presentation Notes

Note that this is a bigger scale than what we saw for developed markets, so these country increases in risk are generally on the same order of magnitude

Q2 Saw The Biggest Increase of China’s Risk

19

Source: Axioma, Inc.

Change in Extra-Market Country Risk: Emerging


-30%

-10%

10%

30%

50%

70%

90%

110%

130%

150%Q4 through 05-Nov-2015 Q3 2015 Q2 2015

Presenter

Presentation Notes

Note that this is a bigger scale than what we saw for developed markets, so these country increases in risk are generally on the same order of magnitude

Managing China’s Risk Continues to be Challenging


0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

10/19/2015 9/17/2015 6/30/15 12/31/2014

China's Role in FTSE Emerging Markets

Capitalization Weight Percent of Risk

EM Risk is Currently More Diverse


Source: Axioma Inc.

-25%

-15%

-5%

5%

15%

25%

35%

0% 10% 20% 30% 40% 50%

June 30, 2015 DevelopedEmergingAverage DevelopedAverage Emerging

Greece

China

-25%

-15%

-5%

5%

15%

25%

35%

0% 10% 20% 30% 40% 50%

November 5, 2015 DevelopedEmergingAverage DevelopedAverage Emerging

Greece

China

EM Risk Recently Rose Sharply in H1 But Then Settled Down Relative to DM


Source: FTSE, Axioma Inc.

Emerging vs. Developed Risk

0.5

0.7

0.9

1.1

1.3

1.5

1.7

1.9

2007 2008 2009 2010 2011 2012 2013 2014 2015

Presenter

Presentation Notes

The ratio of emerging to developed is still almost at parity, and well below the long term average. This may have implications for risk rebalances in all-world portfolios, though. STOP

Brazil’s Yield Curves Shifted Up

© Copyright, Axioma, Inc. 2015. All rights reserved. 23 Source: Markit, Axioma, Inc.

10.00%

11.00%

12.00%

13.00%

14.00%

15.00%

0 10 20 30

Brazil

9.00%

9.50%

10.00%

10.50%

11.00%

0 10 20 30

Russia

6.50%

7.00%

7.50%

8.00%

8.50%

0 10 20 30

India

0.00%

1.00%

2.00%

3.00%

4.00%

5.00%

0 10 20 30

China

Equity Markets Were Positively Correlated With Each Other – And With Bonds…


Q3 Realized Correlations

-1 0 1

Russell 1000FTSE Dev Europe

FTSE Asia Pac…FTSE Japan

FTSE DevelopedFTSE Emerging

GBPEURJPY

GBP Gov.10YUSD Gov.10YJPY Gov.10Y

EUR Gov.10YBrent Crude

Gold

Russell 1000

-1 0 1

FTSE Dev Eur

-1 0 1

FTSE AP ex JP -1 0 1

FTSE Japan -1 0 1

FTSE Emerg

-1 0 1

GBP

-1 0 1

EUR

-1 0 1

JPY -1 0 1




GBPEURJPY



Gold

USD Gov.10Y

-1 0 1

GBP Gov.10Y

-1 0 1

EUR Gov.10Y

-1 0 1

JPY Gov.10Y

-1 0 1

FTSE Devel

…But Correlations Changed A Lot Recently


Change in Correlation From Q2

-1 0 1




GBPEURJPY



Gold

Russell 1000

-1 0 1

FTSE Dev Eur

-1 0 1

FTSE AP ex JP

-1 0 1FTSE Japan

-1 0 1FTSE Emerg

-1 0 1

GBP

-1 0 1

EUR

-1 0 1

JPY -1 0 1




GBPEURJPY



Gold

USD Gov.10Y

-1 0 1

GBP Gov.10Y

-1 0 1

EUR Gov.10Y

-1 0 1

JPY Gov.10Y

-1 0 1FTSE Devel

Source: FTSE, Russell Investments, Standard and Poor’s China Securities Index Company Ltd., Axioma Inc.

Asset Correlations Shot Up Sharply Globally…


FTSE Global Developed

FTSE Emerging

Median realized correlations Percent of correlations that were negative

Percent of correlations that were negative Median realized correlations

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

2000 2002 2004 2006 2008 2010 2012 20140%

5%

10%

15%

20%

25%

30%

35%

40%

45%

2000 2002 2004 2006 2008 2010 2012 2014

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

2000 2002 2004 2006 2008 2010 2012 20140%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

2000 2002 2004 2006 2008 2010 2012 2014

Presenter

Presentation Notes

We just saw the impact of risk model correlations, here are charts showing realized correlations, as measured by the median 60-day pairwise correlation in various benchmarks. With the exception of Japan, correlations remained relatively low as compared with history, although they did increase during the fourth quarter. Europe stands out with a substantial increase in correlation Stop for questions

Source: FTSE, Russell Investments, Standard and Poor’s China Securities Index Company Ltd., Axioma Inc.

…But Slightly Less in Large-Cap US


Median correlations

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

2000 2002 2004 2006 2008 2010 2012 2014

Russell 1000

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

2000 2002 2004 2006 2008 2010 2012 2014

Russell 2000

0%

5%

10%

15%

20%

25%

30%

35%

40%

2000 2002 2004 2006 2008 2010 2012 2014

Percent of Correlations That Were Negative

Presenter

Presentation Notes

We just saw the impact of risk model correlations, here are charts showing realized correlations, as measured by the median 60-day pairwise correlation in various benchmarks. With the exception of Japan, correlations remained relatively low as compared with history, although they did increase during the fourth quarter. Europe stands out with a substantial increase in correlation Stop for questions

High Correlations Can Theoretically Benefit Some Strategies While Hurting Others


Some “rules of thumb” regarding correlation and risk. These won’t always be observed in practice, but all other things being equal, as correlations increase… • Total risk of long only portfolios tends to increase

• Total risk of 100% long-short (dollar neutral) portfolios tends to decrease

The short positions become a better hedge for the long positions

• Total risk of 130/30 portfolios tends to increase

The decrease in the long-short portion of the portfolio is dominated by the increase in the long only portion

• Active risk tends to decrease

Active positions around a benchmark form a long-short portfolio

• The diversification benefit of adding more stocks decreases

• Portfolios will have a higher proportion of factor risk (and a lower proportion of stock-

specific risk)

Source: FTSE, Russell Investments, Standard & Poor's, China Securities Index Company, Ltd, Axioma Inc.

Q3 Asset Dispersion Was Generally Higher Than Average (Good News for Stock Pickers!)


0%

2%

4%

6%

8%

10%

12%

14%

Russell 1000 Russell 2000 FTSEDeveloped

Europe

FTSE AsiaPacific

FTSE Japan CSI 300 ASX 200 FTSEDeveloped

FTSEEmerging

Average Monthly Asset Dispersion Q3 2015 Q2 2015

Q1 2015 Long-Term

0%

1%

2%

3%

4%

US Europe Asia ex-Japan Japan China Australia Worldwide Emerging

Average Monthly Style Factor Dispersion

Q3 2015 Q2 2015

Q1 2015 Long-Term

Presenter

Presentation Notes

We view dispersion as a better measure of the opportunities available to managers, especially stock pickers. The bigger the difference between the best and worst performing stocks the bigger potential reward there is to good stock picking.

7 Key Takeaways for Portfolio Managers


• Style factor investing has been challenging

• US small caps now less risky than large cap

• Currency and country risks have changed, some dramatically • Emerging market risk has become more disperse

• Correlations have changed substantially

• China presents risk challenges • Cross asset-class correlations have moved

Daily Risk Monitors

• We provide daily risk monitors for – US – Canada – UK new – Europe – Asia-Pacific ex-Japan – Japan – China – Australia – Taiwan – Emerging Markets – Global Developed

• Look on www.axioma.com for daily updates of this data • Sign up to get a weekly reminder about the reports


http://www.axioma.com/

Major Themes

• Risk rose since the end of Q2, doubling or more for most benchmarks – TSX Composite, ASX 200 had lowest risk of the major benchmarks we track – Russell 2000 risk fell below that of Russell 1000

• Factor performance varied widely by region, and some factors had returns that fell into the top or bottom percentiles relative to history – Momentum fell apart after quarter-end, with the worst 5-day period ever for the

EU, WW and JP models at one point in the first half of October – At the same time Volatility had among its highest returns (contrary to

expectations) across most regions. During the market downturn in August returns to Volatility were extremely negative in most parts of the world.

• Emerging market risk shot up earlier in Q3, but recently developed markets saw bigger increases, and dispersion in risk across emerging markets has increased

• China’s risk ballooned this year, and its changing proportion of benchmark risk has presented challenges for managers investing in China

• Asset correlations have increased substantially, in some cases to higher levels than during the financial crisis -- meaning more total risk, more factor risk, probably less active risk all other things equal

• Changes in the components of risk (correlations, volatility, and specific factors like emerging vs. developed, small vs. large and currency markets) meant big changes in active risk as well


Presenter

Presentation Notes

There seemed to be a kind of harmonic convergence of issues that drove risk higher

Contact Us For more information on any of these slides or any of Axioma’s other offerings, please contact your account representative or [email protected] I can also be reached at [email protected] or 212-991-4507


mailto:[email protected]

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The Current Risk Landscape - web1.amchouston.comweb1.amchouston.com/flexshare/001/CFA/2015 Presentations/CFA_… · The Current Risk Landscape Axioma Insight Findings Q3 and October