Correlation Between USWE SPORTS and Postal Savings
Can any of the company-specific risk be diversified away by investing in both USWE SPORTS and Postal Savings at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining USWE SPORTS and Postal Savings into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between USWE SPORTS AB and Postal Savings Bank, you can compare the effects of market volatilities on USWE SPORTS and Postal Savings and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in USWE SPORTS with a short position of Postal Savings. Check out your portfolio center. Please also check ongoing floating volatility patterns of USWE SPORTS and Postal Savings.
Diversification Opportunities for USWE SPORTS and Postal Savings
0.63 | Correlation Coefficient |
Poor diversification
The 3 months correlation between USWE and Postal is 0.63. Overlapping area represents the amount of risk that can be diversified away by holding USWE SPORTS AB and Postal Savings Bank in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Postal Savings Bank and USWE SPORTS is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on USWE SPORTS AB are associated (or correlated) with Postal Savings. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Postal Savings Bank has no effect on the direction of USWE SPORTS i.e., USWE SPORTS and Postal Savings go up and down completely randomly.
Pair Corralation between USWE SPORTS and Postal Savings
Assuming the 90 days horizon USWE SPORTS AB is expected to under-perform the Postal Savings. In addition to that, USWE SPORTS is 1.72 times more volatile than Postal Savings Bank. It trades about -0.06 of its total potential returns per unit of risk. Postal Savings Bank is currently generating about 0.19 per unit of volatility. If you would invest 56.00 in Postal Savings Bank on November 29, 2024 and sell it today you would earn a total of 4.00 from holding Postal Savings Bank or generate 7.14% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
USWE SPORTS AB vs. Postal Savings Bank
Performance |
| Timeline |
| USWE SPORTS AB |
| Postal Savings Bank |
USWE SPORTS and Postal Savings Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with USWE SPORTS and Postal Savings
The main advantage of trading using opposite USWE SPORTS and Postal Savings positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if USWE SPORTS position performs unexpectedly, Postal Savings can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Postal Savings will offset losses from the drop in Postal Savings' long position.| USWE SPORTS vs. CAREER EDUCATION | USWE SPORTS vs. Grand Canyon Education | USWE SPORTS vs. DeVry Education Group | USWE SPORTS vs. VITEC SOFTWARE GROUP |
| Postal Savings vs. Merit Medical Systems | Postal Savings vs. Advanced Medical Solutions | Postal Savings vs. SILICON LABORATOR | Postal Savings vs. Sinopec Shanghai Petrochemical |
Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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