Correlation Between Franklin Mutual and Templeton Emerging
Can any of the company-specific risk be diversified away by investing in both Franklin Mutual and Templeton Emerging 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 Franklin Mutual and Templeton Emerging into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Franklin Mutual Global and Templeton Emerging Markets, you can compare the effects of market volatilities on Franklin Mutual and Templeton Emerging 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 Franklin Mutual with a short position of Templeton Emerging. Check out your portfolio center. Please also check ongoing floating volatility patterns of Franklin Mutual and Templeton Emerging.
Diversification Opportunities for Franklin Mutual and Templeton Emerging
0.54 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Franklin and Templeton is 0.54. Overlapping area represents the amount of risk that can be diversified away by holding Franklin Mutual Global and Templeton Emerging Markets in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Templeton Emerging and Franklin Mutual 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 Franklin Mutual Global are associated (or correlated) with Templeton Emerging. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Templeton Emerging has no effect on the direction of Franklin Mutual i.e., Franklin Mutual and Templeton Emerging go up and down completely randomly.
Pair Corralation between Franklin Mutual and Templeton Emerging
Assuming the 90 days horizon Franklin Mutual Global is expected to under-perform the Templeton Emerging. In addition to that, Franklin Mutual is 2.47 times more volatile than Templeton Emerging Markets. It trades about -0.19 of its total potential returns per unit of risk. Templeton Emerging Markets is currently generating about -0.21 per unit of volatility. If you would invest 1,472 in Templeton Emerging Markets on September 24, 2024 and sell it today you would lose (91.00) from holding Templeton Emerging Markets or give up 6.18% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Franklin Mutual Global vs. Templeton Emerging Markets
Performance |
Timeline |
Franklin Mutual Global |
Templeton Emerging |
Franklin Mutual and Templeton Emerging Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Franklin Mutual and Templeton Emerging
The main advantage of trading using opposite Franklin Mutual and Templeton Emerging positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Franklin Mutual position performs unexpectedly, Templeton Emerging 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 Templeton Emerging will offset losses from the drop in Templeton Emerging's long position.Franklin Mutual vs. Deutsche Real Estate | Franklin Mutual vs. Nomura Real Estate | Franklin Mutual vs. Short Real Estate | Franklin Mutual vs. Nexpoint Real Estate |
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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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