Correlation Between Putnam Master and BlackRock Energy
Can any of the company-specific risk be diversified away by investing in both Putnam Master and BlackRock Energy 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 Putnam Master and BlackRock Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Putnam Master Intermediate and BlackRock Energy and, you can compare the effects of market volatilities on Putnam Master and BlackRock Energy 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 Putnam Master with a short position of BlackRock Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Putnam Master and BlackRock Energy.
Diversification Opportunities for Putnam Master and BlackRock Energy
0.73 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Putnam and BlackRock is 0.73. Overlapping area represents the amount of risk that can be diversified away by holding Putnam Master Intermediate and BlackRock Energy and in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BlackRock Energy and Putnam Master 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 Putnam Master Intermediate are associated (or correlated) with BlackRock Energy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of BlackRock Energy has no effect on the direction of Putnam Master i.e., Putnam Master and BlackRock Energy go up and down completely randomly.
Pair Corralation between Putnam Master and BlackRock Energy
Considering the 90-day investment horizon Putnam Master Intermediate is expected to generate 0.63 times more return on investment than BlackRock Energy. However, Putnam Master Intermediate is 1.59 times less risky than BlackRock Energy. It trades about 0.06 of its potential returns per unit of risk. BlackRock Energy and is currently generating about 0.01 per unit of risk. If you would invest 324.00 in Putnam Master Intermediate on December 4, 2024 and sell it today you would earn a total of 7.00 from holding Putnam Master Intermediate or generate 2.16% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Putnam Master Intermediate vs. BlackRock Energy and
Performance |
Timeline |
Putnam Master Interm |
BlackRock Energy |
Putnam Master and BlackRock Energy Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Putnam Master and BlackRock Energy
The main advantage of trading using opposite Putnam Master and BlackRock Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Putnam Master position performs unexpectedly, BlackRock Energy 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 BlackRock Energy will offset losses from the drop in BlackRock Energy's long position.Putnam Master vs. MFS High Income | Putnam Master vs. MFS Investment Grade | Putnam Master vs. Eaton Vance National | Putnam Master vs. MFS 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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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