Correlation Between Structured Products and DBA Sempra
Can any of the company-specific risk be diversified away by investing in both Structured Products and DBA Sempra 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 Structured Products and DBA Sempra into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Structured Products Corp and DBA Sempra 5750, you can compare the effects of market volatilities on Structured Products and DBA Sempra 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 Structured Products with a short position of DBA Sempra. Check out your portfolio center. Please also check ongoing floating volatility patterns of Structured Products and DBA Sempra.
Diversification Opportunities for Structured Products and DBA Sempra
0.03 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Structured and DBA is 0.03. Overlapping area represents the amount of risk that can be diversified away by holding Structured Products Corp and DBA Sempra 5750 in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on DBA Sempra 5750 and Structured Products 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 Structured Products Corp are associated (or correlated) with DBA Sempra. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of DBA Sempra 5750 has no effect on the direction of Structured Products i.e., Structured Products and DBA Sempra go up and down completely randomly.
Pair Corralation between Structured Products and DBA Sempra
Considering the 90-day investment horizon Structured Products Corp is expected to generate 3.51 times more return on investment than DBA Sempra. However, Structured Products is 3.51 times more volatile than DBA Sempra 5750. It trades about 0.02 of its potential returns per unit of risk. DBA Sempra 5750 is currently generating about 0.04 per unit of risk. If you would invest 2,513 in Structured Products Corp on August 31, 2024 and sell it today you would earn a total of 365.00 from holding Structured Products Corp or generate 14.52% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 97.49% |
| Values | Daily Returns |
Structured Products Corp vs. DBA Sempra 5750
Performance |
| Timeline |
| Structured Products Corp |
| DBA Sempra 5750 |
Structured Products and DBA Sempra Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Structured Products and DBA Sempra
The main advantage of trading using opposite Structured Products and DBA Sempra positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Structured Products position performs unexpectedly, DBA Sempra 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 DBA Sempra will offset losses from the drop in DBA Sempra's long position.| Structured Products vs. HUMANA INC | Structured Products vs. SCOR PK | Structured Products vs. Aquagold International | Structured Products vs. Thrivent High Yield |
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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 Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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