Correlation Between Putnam Convertible and Midcap Fund
Can any of the company-specific risk be diversified away by investing in both Putnam Convertible and Midcap Fund 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 Convertible and Midcap Fund into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Putnam Convertible Incm Gwth and Midcap Fund Class, you can compare the effects of market volatilities on Putnam Convertible and Midcap Fund 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 Convertible with a short position of Midcap Fund. Check out your portfolio center. Please also check ongoing floating volatility patterns of Putnam Convertible and Midcap Fund.
Diversification Opportunities for Putnam Convertible and Midcap Fund
0.77 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Putnam and Midcap is 0.77. Overlapping area represents the amount of risk that can be diversified away by holding Putnam Convertible Incm Gwth and Midcap Fund Class in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Midcap Fund Class and Putnam Convertible 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 Convertible Incm Gwth are associated (or correlated) with Midcap Fund. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Midcap Fund Class has no effect on the direction of Putnam Convertible i.e., Putnam Convertible and Midcap Fund go up and down completely randomly.
Pair Corralation between Putnam Convertible and Midcap Fund
Assuming the 90 days horizon Putnam Convertible Incm Gwth is expected to generate 0.64 times more return on investment than Midcap Fund. However, Putnam Convertible Incm Gwth is 1.56 times less risky than Midcap Fund. It trades about -0.1 of its potential returns per unit of risk. Midcap Fund Class is currently generating about -0.14 per unit of risk. If you would invest 2,616 in Putnam Convertible Incm Gwth on November 29, 2024 and sell it today you would lose (104.00) from holding Putnam Convertible Incm Gwth or give up 3.98% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Putnam Convertible Incm Gwth vs. Midcap Fund Class
Performance |
Timeline |
Putnam Convertible Incm |
Midcap Fund Class |
Putnam Convertible and Midcap Fund Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Putnam Convertible and Midcap Fund
The main advantage of trading using opposite Putnam Convertible and Midcap Fund positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Putnam Convertible position performs unexpectedly, Midcap Fund 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 Midcap Fund will offset losses from the drop in Midcap Fund's long position.Putnam Convertible vs. Transamerica Asset Allocation | Putnam Convertible vs. Calvert Moderate Allocation | Putnam Convertible vs. Pnc Balanced Allocation | Putnam Convertible vs. Dodge Cox Stock |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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