Correlation Between Templeton Global and Putnam Global
Can any of the company-specific risk be diversified away by investing in both Templeton 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 Templeton 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 Templeton Global Bond and Putnam Global Incm, you can compare the effects of market volatilities on Templeton 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 Templeton Global with a short position of Putnam Global. Check out your portfolio center. Please also check ongoing floating volatility patterns of Templeton Global and Putnam Global.
Diversification Opportunities for Templeton Global and Putnam Global
0.96 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Templeton and Putnam is 0.96. Overlapping area represents the amount of risk that can be diversified away by holding Templeton Global Bond and Putnam Global Incm in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Putnam Global Incm and Templeton 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 Templeton Global Bond 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 Incm has no effect on the direction of Templeton Global i.e., Templeton Global and Putnam Global go up and down completely randomly.
Pair Corralation between Templeton Global and Putnam Global
Assuming the 90 days horizon Templeton Global Bond is expected to under-perform the Putnam Global. In addition to that, Templeton Global is 3.19 times more volatile than Putnam Global Incm. It trades about -0.1 of its total potential returns per unit of risk. Putnam Global Incm is currently generating about -0.09 per unit of volatility. If you would invest 1,010 in Putnam Global Incm on August 28, 2024 and sell it today you would lose (4.00) from holding Putnam Global Incm or give up 0.4% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Templeton Global Bond vs. Putnam Global Incm
Performance |
Timeline |
Templeton Global Bond |
Putnam Global Incm |
Templeton Global and Putnam Global Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Templeton Global and Putnam Global
The main advantage of trading using opposite Templeton Global and Putnam Global positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Templeton 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.Templeton Global vs. Franklin Mutual Beacon | Templeton Global vs. Templeton Developing Markets | Templeton Global vs. Franklin Mutual Global | Templeton Global vs. Franklin Mutual Global |
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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 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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