INTERACTIVE

RiskWatch for January 22, 2018

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 models. One 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 can be a major driver of risk in multicountry benchmarks and can often change substantially from one quarter to the next. 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. Note that the following charts are now using Axioma's new WW4 (worldwide) model: predicted volatility by currency, predicted volatility by country and country-country correlations. Data are as of Dec. 29, 2017. Change compares to the previous quarter.
U.S. market volatility*
U.S. indexesCurrentChange
Russell 1000 6.2 -1.3
Russell 2000 10.1 -2.0
 
U.S. sectorsCurrentChange
Energy 17.70 -1.20
Telecommunication services 16.70 1.00
Financials 11.90 -1.50
Utilities 10.40 0.40
Information technology 10.20 -1.00
Real estate 10.00 -0.30
Industrials 9.60 -0.80
Health care 9.40 -1.20
Materials 9.40 -1.10
Consumer discretionary 8.60 -0.90
Consumer staples 8.00 0.00
Index volatility
Predicted volatility by currency**
Developed markets
10 most volatileCurrentChange
New Zealand dollar 8.71 -0.24
British pound 8.07 -0.79
Norwegian krone 7.75 -0.04
Japanese yen 7.67 -1.08
Swedish krona 7.44 -0.24
Australian dollar 7.30 -0.43
Canadian dollar 6.76 -0.22
Euro 6.43 -0.47
Swiss franc 6.42 -0.55
Danish krone 6.41 -0.45
 
Emerging markets
10 most volatileCurrentChange
South African rand 14.66 0.55
Turkish lira 10.96 0.12
Mexican peso 10.72 0.28
Brazilian real 10.51 -0.18
Russian ruble 9.90 -1.22
Colombian peso 8.76 -1.18
Polish zloty 8.14 -0.30
Chilean peso 8.11 0.38
Hungarian forint 7.94 -0.07
Czech koruna 7.13 0.04
Predicted volatility by country**
Developed markets
5 most volatileCurrentChange
Spain 11.29 0.13
Ireland 10.94 -1.29
Japan 10.79 -0.89
Italy 10.21 -1.77
South Korea 10.16 0.48
 
5 least volatileCurrentChange
Canada 6.04 -1.46
Singapore 6.85 -0.84
New Zealand 6.94 -1.46
United States 7.04 -1.54
Australia 7.15 -1.46
Emerging markets
5 most volatileCurrentChange
Greece 20.56 0.24
Qatar 19.46 0.95
Pakistan 18.04 -1.41
Egypt 17.78 0.60
Chile 17.16 6.55
 
5 least volatileCurrentChange
Czech Republic 7.94 -0.44
Malaysia 8.48 -0.40
Mexico 9.21 0.33
Colombia 9.50 -0.29
Russian Federation 9.62 -0.29
Country-country correlations***
Developed markets
Highest correlationsCurrent
France Germany 0.82
France Netherlands 0.78
France Italy 0.78
Germany Netherlands 0.74
Germany Belgium 0.72
 
Lowest correlationsCurrent
U.S. Hong Kong -0.51
U.S. Norway -0.47
Spain U.S. -0.47
U.S. United Kingdom -0.47
U.S. Sweden -0.46
Emerging markets
Highest correlationsCurrent
Czech Republic Hungary 0.27
Mexico Colombia 0.26
Russian Federation Morocco 0.23
Philippines Morocco 0.23
Peru Colombia 0.21
 
Lowest correlationsCurrent
China India -0.30
China Mexico -0.25
India Taiwan -0.25
China Brazil -0.24
India Russian Federation -0.23
Correlations plummet
Correlations measure how closely stocks move together. High correlations suggest that some global force (such as a financial crisis) is pushing all stocks in the same direction. When the correlation is low — as we see currently — it suggests that each stock move is based on its own characteristics, not a theme. Low correlation theoretically is better for stock-pickers because prices change based on their fundamentals; that also serves to keep overall volatility low (one stock rises and the other falls but the combination of the two doesn't move). This chart shows the median correlation of 60-day returns across all asset pairs in the FTSE Developed index.
Multiasset-class data
Risk
LevelChangeStandard deviationChange
U.S. 10-year T-note (yield) 2.41% 6.77 bps 53.25% -0.06%
U.S. inv.-grade (spread) 54 bps -4.37 bps 25.39% -0.02%
U.S. high-yield (spread) 267 bps -3.47 bps 52.83% -0.04%
European gov't 10-year (yield) 0.48% -1.54 bps 48.55% -0.04%
European inv.-grade (spread) 57 bps -7.78 bps 36.08% -0.01%
European high-yield (spread) 195 bps -13.72 bps 84.47% -0.05%
Euro 1.20 1.57 6.43% -0.47%
British pound 1.35 0.83 8.07% -0.79%
Japanese yen 112.65 0.08 7.67% -1.08%
Asset-class correlations
U.S.
10-year
T-note
U.S.
investment
grade
U.S.
high
yield
Euro
gov't
10-year
Euro
investment
grade
Euro
high
yield
Russell 1000Russell 2000FTSEEuroPoundYen
U.S. 10-year T-note (yield) 1.00 -0.21 -0.63 0.68 -0.23 -0.11 0.38 0.40 0.26 -0.20 -0.14 -0.53
U.S. inv.-grade (spread) -0.21 1.00 0.55 -0.09 0.15 0.17 -0.27 -0.21 -0.24 0.01 -0.01 0.14
U.S. high-yield (spread) -0.63 0.55 1.00 -0.45 0.19 0.19 -0.46 -0.43 -0.46 0.12 0.07 0.40
European gov't 10-year (yield) 0.68 -0.09 -0.45 1.00 -0.31 -0.18 0.16 0.21 0.17 0.03 0.04 -0.44
European inv.-grade (spread) -0.23 0.15 0.19 -0.31 1.00 0.51 -0.12 -0.11 -0.17 -0.12 0.00 0.14
European high-yield (spread) -0.11 0.17 0.19 -0.18 0.51 1.00 -0.05 -0.05 -0.13 -0.05 -0.08 0.14
Euro -0.20 0.01 0.12 0.03 -0.12 -0.05 -0.16 -0.12 0.18 1.00 0.51 0.56
British pound -0.14 -0.01 0.07 0.04 0.00 -0.08 -0.11 -0.08 0.14 0.51 1.00 0.33
Japanese yen -0.53 0.14 0.40 -0.44 0.14 0.14 -0.30 -0.27 -0.07 0.56 0.33 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.
*US4 medium-horizon fundamental forecast.
**Numeraire: U.S. dollar.
***In excess of the global market.
Source: Axioma