INTERACTIVE

Riskwatch for Q2 2017

RiskWatch provides recent data on volatility and correlation, the two components of risk, for U.S. and global equity and fixed-income markets. The equity data are derived from Axioma's medium-term fundamental risk model. The first set of tables is designed to capture U.S. market sectors plus countries and currencies with the highest and lowest levels of volatility and how that component of risk has changed since the end of the prior quarter. The highest and lowest correlated countries within developed and emerging markets are also highlighted. Another table illustrates how currency volatility has been a major driver of risk in multicountry benchmarks as well as a cause for concern in individual countries. The fixed-income data, detailed in the multiasset-class section, consist of U.S. and eurozone government yields, investment-grade and subinvestment-grade spreads as well as correlations among those asset classes and selected currencies. Data are as of March 31, 2017. Change compares to the previous quarter.
U.S. market volatility*
U.S. indexesCurrentChange
Russell 1000 9.0 -1.5
Russell 2000 14.2 -1.3
U.S. sectorsCurrentChange
Energy 19.1 -3.9
Financials 14.8 -1.0
Telecommunication services 14.5 -0.5
Real estate 13.8 -1.6
Materials 13.1 -0.7
Health care 12.8 -1.7
Utilities 12.3 -2.3
Industrials 12.2 -0.9
Information technology 11.5 -2.1
Consumer discretionary 10.4 -1.9
Consumer staples 8.9 -1.1
*US4 risk model forecast
Index volatility
Predicted volatility by currency*
Developed markets
10 most volatileCurrentChange
British pound 11.2 -0.8
Japanese yen 11.1 -0.4
New Zealand dollar 10.4 -0.8
Norwegian krone 10.4 -0.6
Australian dollar 9.5 -0.6
Swedish krona 9.4 -0.1
South Korean won 9.2 0.2
Euro 8.5 -0.5
Danish krone 8.4 -0.5
Canadian dollar 8.4 -0.5
Emerging markets**
10 most volatileCurrentChange
South African rand 18.8 -0.5
Brazilian real 16.0 -1.8
Colombian peso 15.4 -1.3
Mexican peso 15.0 -0.2
Turkish lira 13.8 2.6
Russian ruble 13.6 -2.6
Polish zloty 10.4 -0.8
Hungarian forint 10.2 -0.5
Chilean peso 10.0 -0.6
Romanian new leu 8.7 -0.4
Predicted volatility by country*
Developed markets
5 most volatileCurrentChange
Italy 16.5 -1.4
Portugal 15.4 -1.8
Japan 14.8 -2.5
Spain 14.7 -2.3
Peru 13.8 -0.9
5 least volatileCurrentChange
Canada 9.4 -1.0
New Zealand 10.2 -1.6
South Korea 10.2 -2.4
Singapore 10.3 -1.5
Hong Kong 10.5 -2.2
Emerging markets**
5 most volatileCurrentChange
Egypt 26.9 -1.4
Greece 23.4 -1.9
Brazil 15.9 -1.3
United Arab Emirates 15.5 -1.3
Turkey 15.3 -3.4
5 least volatileCurrentChange
Czech Republic 9.2 -1.5
Malaysia 9.4 -1.2
Hungary 9.9 -1.0
Chile 10.8 -0.4
Russian Federation 10.8 -0.1
Country-country correlations**
Developed markets
Highest correlationsCurrent
France Netherlands 0.78
France Germany 0.78
Spain France 0.76
France Italy 0.75
Spain Italy 0.73
Lowest correlationsCurrent
Spain U.S. -0.43
U.S. South Korea -0.40
U.S. Japan -0.38
U.S. Hong Kong -0.34
U.S. Italy -0.33
Emerging markets
Highest correlationsCurrent
Czech Republic Hungary 0.31
Pakistan Morocco 0.31
Mexico Chile 0.27
Poland Hungary 0.27
Mexico Colombia 0.26
Lowest correlationsCurrent
China Mexico -0.33
South Africa India -0.29
China Thailand -0.29
China Indonesia -0.28
China South Africa -0.25
Trump surprise
When Donald Trump was elected president in November, many predicted gloom and doom for the stock market. But stocks defied expectations. In the U.S., stocks have risen more than 10% since the November election, and more than 5% since the end of 2016, with expected winners from shifting policies (such as financial stocks) leading the way. As stock prices ratcheted up, their volatility fell -- also unexpected given the high level of uncertainty about what the policies might be and their potential impact. Most surprising, however, is that the volatility of those sectors not expected to benefit or to be hurt by those policies has fallen the most. With the exception of energy, whose fortunes are more closely tied to oil prices than to government actions, the sectors that have fared the best have seen much more muted decreases in their risk. Below is a chart showing the change in expected volatility since the end of 2016.
Multiasset-class data
Risk
LevelChangeStandard deviationChange
U.S. 10-year T-note (yield) 2.42% -3.45 bps 66.01% -0.02%
U.S. inv. grade (spread) 60 bps -6.83 bps 20.52% -0.01%
U.S. high yield (spread) 294 bps 138.8 bps 85.08% -0.34%
European gov't 10-year (yield) 0.34% 10.14 bps 55.57% -0.01%
European inv. grade (spread) 74 bps -0.24 bps 32.64% 0.04%
European high yield (spread) 256 bps 122.94 bps 92.81% -0.21%
Euro** 1.07 1.4% 8.47% -0.46%
British pound** 1.25 1.2% 11.17% -0.79%
Japanese yen** 111.43 -4.46% 11.07% -0.38%
Asset-class correlations
 U.S.
10-year
U.S.
inv. grade
U.S. high yieldEuro gov't
10-year
Euro
inv. grade
Euro high yieldRussell 1000Russell 2000FTSEEuroPoundYen
U.S. 10-year T-note (yield) 1.00 -0.19 -0.58 0.68 -0.35 -0.22 0.34 0.39 0.29 -0.13 0.19 -0.48
U.S. inv. grade (spread) -0.19 1.00 0.49 -0.15 0.17 0.29 -0.18 -0.13 -0.33 -0.20 -0.25 0.13
U.S. high yield (spread) -0.58 0.49 1.00 -0.42 0.29 0.47 -0.53 -0.47 -0.69 -0.14 -0.38 0.35
European gov't 10-year (yield) 0.68 -0.15 -0.42 1.00 -0.44 -0.29 0.18 0.19 0.20 -0.01 0.20 -0.41
European inv. grade (spread) -0.35 0.17 0.29 -0.44 1.00 0.54 -0.06 -0.06 -0.13 -0.10 -0.15 0.19
European high yield (spread) -0.22 0.29 0.47 -0.29 0.54 1.00 -0.22 -0.16 -0.43 -0.22 -0.39 0.20
Euro** -0.13 -0.20 -0.14 -0.01 -0.10 -0.22 0.06 -0.03 0.34 1.00 0.60 0.44
British pound** 0.19 -0.25 -0.38 0.20 -0.15 -0.39 0.32 0.26 0.58 0.60 1.00 -0.01
Japanese yen** -0.48 0.13 0.35 -0.41 0.19 0.20 -0.30 -0.31 -0.21 0.44 -0.01 1.00
U.S. and euro spread curves are defined as the spread over the swap curve (previously spread over the government curve). Emerging markets sections include only countries in the FTSE Emerging Markets index.
*Numeraire: U.S. dollar.
**In excess of the global market.
Source: Axioma