Correlation Between Templeton Emerging and Franklin Total
Can any of the company-specific risk be diversified away by investing in both Templeton Emerging and Franklin Total 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 Emerging and Franklin Total into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Templeton Emerging Markets and Franklin Total Return, you can compare the effects of market volatilities on Templeton Emerging and Franklin Total 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 Emerging with a short position of Franklin Total. Check out your portfolio center. Please also check ongoing floating volatility patterns of Templeton Emerging and Franklin Total.
Diversification Opportunities for Templeton Emerging and Franklin Total
0.67 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Templeton and Franklin is 0.67. Overlapping area represents the amount of risk that can be diversified away by holding Templeton Emerging Markets and Franklin Total Return in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Franklin Total Return and Templeton Emerging 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 Emerging Markets are associated (or correlated) with Franklin Total. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Franklin Total Return has no effect on the direction of Templeton Emerging i.e., Templeton Emerging and Franklin Total go up and down completely randomly.
Pair Corralation between Templeton Emerging and Franklin Total
Assuming the 90 days horizon Templeton Emerging Markets is expected to under-perform the Franklin Total. In addition to that, Templeton Emerging is 1.58 times more volatile than Franklin Total Return. It trades about -0.06 of its total potential returns per unit of risk. Franklin Total Return is currently generating about -0.05 per unit of volatility. If you would invest 852.00 in Franklin Total Return on September 4, 2024 and sell it today you would lose (8.00) from holding Franklin Total Return or give up 0.94% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Templeton Emerging Markets vs. Franklin Total Return
Performance |
Timeline |
Templeton Emerging |
Franklin Total Return |
Templeton Emerging and Franklin Total Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Templeton Emerging and Franklin Total
The main advantage of trading using opposite Templeton Emerging and Franklin Total positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Templeton Emerging position performs unexpectedly, Franklin Total 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 Franklin Total will offset losses from the drop in Franklin Total's long position.Templeton Emerging vs. Allianzgi Health Sciences | Templeton Emerging vs. Deutsche Health And | Templeton Emerging vs. Prudential Health Sciences | Templeton Emerging vs. Live Oak Health |
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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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