Correlation Between Gabelli Global and Putnam Global
Can any of the company-specific risk be diversified away by investing in both Gabelli Global and Putnam Global 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 Gabelli Global and Putnam Global into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Gabelli Global Financial and Putnam Global Financials, you can compare the effects of market volatilities on Gabelli Global and Putnam Global 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 Gabelli Global with a short position of Putnam Global. Check out your portfolio center. Please also check ongoing floating volatility patterns of Gabelli Global and Putnam Global.
Diversification Opportunities for Gabelli Global and Putnam Global
0.68 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Gabelli and Putnam is 0.68. Overlapping area represents the amount of risk that can be diversified away by holding Gabelli Global Financial and Putnam Global Financials in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Putnam Global Financials and Gabelli 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 Gabelli Global Financial are associated (or correlated) with Putnam Global. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Putnam Global Financials has no effect on the direction of Gabelli Global i.e., Gabelli Global and Putnam Global go up and down completely randomly.
Pair Corralation between Gabelli Global and Putnam Global
Assuming the 90 days horizon Gabelli Global Financial is expected to generate 1.71 times more return on investment than Putnam Global. However, Gabelli Global is 1.71 times more volatile than Putnam Global Financials. It trades about 0.09 of its potential returns per unit of risk. Putnam Global Financials is currently generating about -0.01 per unit of risk. If you would invest 1,535 in Gabelli Global Financial on October 23, 2024 and sell it today you would earn a total of 75.00 from holding Gabelli Global Financial or generate 4.89% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Gabelli Global Financial vs. Putnam Global Financials
Performance |
Timeline |
Gabelli Global Financial |
Putnam Global Financials |
Gabelli Global and Putnam Global Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Gabelli Global and Putnam Global
The main advantage of trading using opposite Gabelli Global and Putnam Global positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Gabelli Global position performs unexpectedly, Putnam Global 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 Global will offset losses from the drop in Putnam Global's long position.Gabelli Global vs. Guggenheim Diversified Income | Gabelli Global vs. Voya Solution Conservative | Gabelli Global vs. Jhancock Diversified Macro | Gabelli Global vs. Allianzgi Diversified Income |
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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 Valuation module to check real value of public entities based on technical and fundamental data.
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