Correlation Between Loomis Sayles and Natixis Us
Can any of the company-specific risk be diversified away by investing in both Loomis Sayles and Natixis Us 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 Loomis Sayles and Natixis Us into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Loomis Sayles Global and Natixis Equity Opportunities, you can compare the effects of market volatilities on Loomis Sayles and Natixis Us 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 Loomis Sayles with a short position of Natixis Us. Check out your portfolio center. Please also check ongoing floating volatility patterns of Loomis Sayles and Natixis Us.
Diversification Opportunities for Loomis Sayles and Natixis Us
0.94 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Loomis and Natixis is 0.94. Overlapping area represents the amount of risk that can be diversified away by holding Loomis Sayles Global and Natixis Equity Opportunities in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Natixis Equity Oppor and Loomis Sayles 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 Loomis Sayles Global are associated (or correlated) with Natixis Us. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Natixis Equity Oppor has no effect on the direction of Loomis Sayles i.e., Loomis Sayles and Natixis Us go up and down completely randomly.
Pair Corralation between Loomis Sayles and Natixis Us
Assuming the 90 days horizon Loomis Sayles Global is expected to generate 0.67 times more return on investment than Natixis Us. However, Loomis Sayles Global is 1.48 times less risky than Natixis Us. It trades about -0.05 of its potential returns per unit of risk. Natixis Equity Opportunities is currently generating about -0.05 per unit of risk. If you would invest 2,427 in Loomis Sayles Global on December 29, 2024 and sell it today you would lose (56.00) from holding Loomis Sayles Global or give up 2.31% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Loomis Sayles Global vs. Natixis Equity Opportunities
Performance |
Timeline |
Loomis Sayles Global |
Natixis Equity Oppor |
Loomis Sayles and Natixis Us Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Loomis Sayles and Natixis Us
The main advantage of trading using opposite Loomis Sayles and Natixis Us positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Loomis Sayles position performs unexpectedly, Natixis Us 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 Natixis Us will offset losses from the drop in Natixis Us' long position.Loomis Sayles vs. Loomis Sayles Global | Loomis Sayles vs. Natixis Equity Opportunities | Loomis Sayles vs. Loomis Sayles Global | Loomis Sayles vs. Loomis Sayles Growth |
Natixis Us vs. Natixis Oakmark Fund | Natixis Us vs. Vaughan Nelson Small | Natixis Us vs. Loomis Sayles Growth | Natixis Us vs. Natixis Equity Opportunities |
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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