Correlation Between Putnam Global and Destinations Core
Can any of the company-specific risk be diversified away by investing in both Putnam Global and Destinations Core 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 Global and Destinations Core into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Putnam Global Financials and Destinations Core Fixed, you can compare the effects of market volatilities on Putnam Global and Destinations Core 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 Global with a short position of Destinations Core. Check out your portfolio center. Please also check ongoing floating volatility patterns of Putnam Global and Destinations Core.
Diversification Opportunities for Putnam Global and Destinations Core
0.8 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Putnam and Destinations is 0.8. Overlapping area represents the amount of risk that can be diversified away by holding Putnam Global Financials and Destinations Core Fixed in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Destinations Core Fixed and Putnam Global 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 Global Financials are associated (or correlated) with Destinations Core. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Destinations Core Fixed has no effect on the direction of Putnam Global i.e., Putnam Global and Destinations Core go up and down completely randomly.
Pair Corralation between Putnam Global and Destinations Core
Assuming the 90 days horizon Putnam Global Financials is expected to under-perform the Destinations Core. In addition to that, Putnam Global is 1.71 times more volatile than Destinations Core Fixed. It trades about -0.1 of its total potential returns per unit of risk. Destinations Core Fixed is currently generating about -0.13 per unit of volatility. If you would invest 846.00 in Destinations Core Fixed on October 11, 2024 and sell it today you would lose (20.00) from holding Destinations Core Fixed or give up 2.36% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Putnam Global Financials vs. Destinations Core Fixed
Performance |
Timeline |
Putnam Global Financials |
Destinations Core Fixed |
Putnam Global and Destinations Core Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Putnam Global and Destinations Core
The main advantage of trading using opposite Putnam Global and Destinations Core positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Putnam Global position performs unexpectedly, Destinations Core 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 Destinations Core will offset losses from the drop in Destinations Core's long position.Putnam Global vs. Neuberger Berman Real | Putnam Global vs. Nexpoint Real Estate | Putnam Global vs. Rems Real Estate | Putnam Global vs. Vy Clarion Real |
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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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