Correlation Between Franklin Templeton and Franklin Gold
Can any of the company-specific risk be diversified away by investing in both Franklin Templeton and Franklin Gold 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 Templeton and Franklin Gold into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Franklin Templeton Smacs and Franklin Gold And, you can compare the effects of market volatilities on Franklin Templeton and Franklin Gold 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 Templeton with a short position of Franklin Gold. Check out your portfolio center. Please also check ongoing floating volatility patterns of Franklin Templeton and Franklin Gold.
Diversification Opportunities for Franklin Templeton and Franklin Gold
0.73 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Franklin and Franklin is 0.73. Overlapping area represents the amount of risk that can be diversified away by holding Franklin Templeton Smacs and Franklin Gold And in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Franklin Gold And and Franklin Templeton 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 Templeton Smacs are associated (or correlated) with Franklin Gold. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Franklin Gold And has no effect on the direction of Franklin Templeton i.e., Franklin Templeton and Franklin Gold go up and down completely randomly.
Pair Corralation between Franklin Templeton and Franklin Gold
Assuming the 90 days horizon Franklin Templeton Smacs is expected to generate 0.55 times more return on investment than Franklin Gold. However, Franklin Templeton Smacs is 1.82 times less risky than Franklin Gold. It trades about -0.13 of its potential returns per unit of risk. Franklin Gold And is currently generating about -0.26 per unit of risk. If you would invest 912.00 in Franklin Templeton Smacs on August 31, 2024 and sell it today you would lose (29.00) from holding Franklin Templeton Smacs or give up 3.18% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Franklin Templeton Smacs vs. Franklin Gold And
Performance |
| Timeline |
| Franklin Templeton Smacs |
| Franklin Gold And |
Franklin Templeton and Franklin Gold Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Franklin Templeton and Franklin Gold
The main advantage of trading using opposite Franklin Templeton and Franklin Gold positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Franklin Templeton position performs unexpectedly, Franklin Gold 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 Gold will offset losses from the drop in Franklin Gold's long position.| Franklin Templeton vs. Ab Bond Inflation | Franklin Templeton vs. Ab Bond Inflation | Franklin Templeton vs. Guidepath Managed Futures | Franklin Templeton vs. Asg Managed Futures |
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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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