Correlation Between State Street and State Street
Can any of the company-specific risk be diversified away by investing in both State Street and State Street 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 State Street and State Street into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between State Street Target and State Street Target, you can compare the effects of market volatilities on State Street and State Street 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 State Street with a short position of State Street. Check out your portfolio center. Please also check ongoing floating volatility patterns of State Street and State Street.
Diversification Opportunities for State Street and State Street
0.97 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between State and State is 0.97. Overlapping area represents the amount of risk that can be diversified away by holding State Street Target and State Street Target in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on State Street Target and State Street 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 State Street Target are associated (or correlated) with State Street. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of State Street Target has no effect on the direction of State Street i.e., State Street and State Street go up and down completely randomly.
Pair Corralation between State Street and State Street
Assuming the 90 days horizon State Street Target is expected to generate 1.29 times more return on investment than State Street. However, State Street is 1.29 times more volatile than State Street Target. It trades about 0.11 of its potential returns per unit of risk. State Street Target is currently generating about 0.11 per unit of risk. If you would invest 1,571 in State Street Target on August 29, 2024 and sell it today you would earn a total of 24.00 from holding State Street Target or generate 1.53% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
State Street Target vs. State Street Target
Performance |
| Timeline |
| State Street Target |
| State Street Target |
State Street and State Street Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with State Street and State Street
The main advantage of trading using opposite State Street and State Street positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if State Street position performs unexpectedly, State Street 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 State Street will offset losses from the drop in State Street's long position.| State Street vs. T Rowe Price | State Street vs. Multisector Bond Sma | State Street vs. Transamerica Funds | State Street vs. Financial Industries Fund |
| State Street vs. Victory High Income | State Street vs. Ppm High Yield | State Street vs. Copeland Risk Managed | State Street vs. Siit High Yield |
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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