Correlation Between Putnam Floating and Putnam Ohio
Can any of the company-specific risk be diversified away by investing in both Putnam Floating and Putnam Ohio 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 Floating and Putnam Ohio into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Putnam Floating Rate and Putnam Ohio Tax, you can compare the effects of market volatilities on Putnam Floating and Putnam Ohio 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 Floating with a short position of Putnam Ohio. Check out your portfolio center. Please also check ongoing floating volatility patterns of Putnam Floating and Putnam Ohio.
Diversification Opportunities for Putnam Floating and Putnam Ohio
-0.13 | Correlation Coefficient |
Good diversification
The 3 months correlation between Putnam and Putnam is -0.13. Overlapping area represents the amount of risk that can be diversified away by holding Putnam Floating Rate and Putnam Ohio Tax in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Putnam Ohio Tax and Putnam Floating 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 Floating Rate are associated (or correlated) with Putnam Ohio. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Putnam Ohio Tax has no effect on the direction of Putnam Floating i.e., Putnam Floating and Putnam Ohio go up and down completely randomly.
Pair Corralation between Putnam Floating and Putnam Ohio
Assuming the 90 days horizon Putnam Floating Rate is expected to generate 0.62 times more return on investment than Putnam Ohio. However, Putnam Floating Rate is 1.61 times less risky than Putnam Ohio. It trades about 0.17 of its potential returns per unit of risk. Putnam Ohio Tax is currently generating about 0.02 per unit of risk. If you would invest 774.00 in Putnam Floating Rate on September 22, 2024 and sell it today you would earn a total of 25.00 from holding Putnam Floating Rate or generate 3.23% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Putnam Floating Rate vs. Putnam Ohio Tax
Performance |
Timeline |
Putnam Floating Rate |
Putnam Ohio Tax |
Putnam Floating and Putnam Ohio Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Putnam Floating and Putnam Ohio
The main advantage of trading using opposite Putnam Floating and Putnam Ohio positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Putnam Floating position performs unexpectedly, Putnam Ohio 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 Putnam Ohio will offset losses from the drop in Putnam Ohio's long position.Putnam Floating vs. Putnam Equity Income | Putnam Floating vs. Putnam Tax Exempt | Putnam Floating vs. Putnam High Yield | Putnam Floating vs. Putnam Massachusetts Tax |
Putnam Ohio vs. Putnam Equity Income | Putnam Ohio vs. Putnam Tax Exempt | Putnam Ohio vs. Putnam Floating Rate | Putnam Ohio vs. Putnam 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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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