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. indexes | Current | Change |
|---|---|---|
| Russell 1000 | 9.0 | -1.5 |
| Russell 2000 | 14.2 | -1.3 |
| U.S. sectors | Current | Change |
|---|---|---|
| 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 volatile | Current | Change |
|---|---|---|
| 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 volatile | Current | Change |
|---|---|---|
| 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 volatile | Current | Change |
|---|---|---|
| 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 volatile | Current | Change |
|---|---|---|
| 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 volatile | Current | Change |
|---|---|---|
| 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 volatile | Current | Change |
|---|---|---|
| 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 correlations | Current | |
|---|---|---|
| France | Netherlands | 0.78 |
| France | Germany | 0.78 |
| Spain | France | 0.76 |
| France | Italy | 0.75 |
| Spain | Italy | 0.73 |
| Lowest correlations | Current | |
|---|---|---|
| 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 correlations | Current | |
|---|---|---|
| Czech Republic | Hungary | 0.31 |
| Pakistan | Morocco | 0.31 |
| Mexico | Chile | 0.27 |
| Poland | Hungary | 0.27 |
| Mexico | Colombia | 0.26 |
| Lowest correlations | Current | |
|---|---|---|
| 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 | ||||
| Level | Change | Standard deviation | Change | |
|---|---|---|---|---|
| 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 yield | Euro gov't 10-year | Euro inv. grade | Euro high yield | Russell 1000 | Russell 2000 | FTSE | Euro | Pound | Yen | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 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
Sponsored
White Papers
Sponsored Content
Partner Content