Correlation Between Scharf Global and Loomis Sayles
Can any of the company-specific risk be diversified away by investing in both Scharf Global and Loomis Sayles 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 Scharf Global and Loomis Sayles into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Scharf Global Opportunity and Loomis Sayles Inflation, you can compare the effects of market volatilities on Scharf Global and Loomis Sayles 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 Scharf Global with a short position of Loomis Sayles. Check out your portfolio center. Please also check ongoing floating volatility patterns of Scharf Global and Loomis Sayles.
Diversification Opportunities for Scharf Global and Loomis Sayles
-0.28 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Scharf and Loomis is -0.28. Overlapping area represents the amount of risk that can be diversified away by holding Scharf Global Opportunity and Loomis Sayles Inflation in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Loomis Sayles Inflation and Scharf 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 Scharf Global Opportunity are associated (or correlated) with Loomis Sayles. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Loomis Sayles Inflation has no effect on the direction of Scharf Global i.e., Scharf Global and Loomis Sayles go up and down completely randomly.
Pair Corralation between Scharf Global and Loomis Sayles
Assuming the 90 days horizon Scharf Global Opportunity is expected to generate 2.01 times more return on investment than Loomis Sayles. However, Scharf Global is 2.01 times more volatile than Loomis Sayles Inflation. It trades about 0.13 of its potential returns per unit of risk. Loomis Sayles Inflation is currently generating about -0.03 per unit of risk. If you would invest 3,597 in Scharf Global Opportunity on September 7, 2024 and sell it today you would earn a total of 175.00 from holding Scharf Global Opportunity or generate 4.87% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 98.44% |
Values | Daily Returns |
Scharf Global Opportunity vs. Loomis Sayles Inflation
Performance |
Timeline |
Scharf Global Opportunity |
Loomis Sayles Inflation |
Scharf Global and Loomis Sayles Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Scharf Global and Loomis Sayles
The main advantage of trading using opposite Scharf Global and Loomis Sayles positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Scharf Global position performs unexpectedly, Loomis Sayles 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 Loomis Sayles will offset losses from the drop in Loomis Sayles' long position.Scharf Global vs. Ab Select Equity | Scharf Global vs. Us Vector Equity | Scharf Global vs. Scharf Balanced Opportunity | Scharf Global vs. Semiconductor Ultrasector Profund |
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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 Analyst Advice module to analyst recommendations and target price estimates broken down by several categories.
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