Correlation Between Simt Multi and Legg Mason
Can any of the company-specific risk be diversified away by investing in both Simt Multi and Legg Mason 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 Simt Multi and Legg Mason into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Simt Multi Asset Inflation and Legg Mason Bw, you can compare the effects of market volatilities on Simt Multi and Legg Mason 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 Simt Multi with a short position of Legg Mason. Check out your portfolio center. Please also check ongoing floating volatility patterns of Simt Multi and Legg Mason.
Diversification Opportunities for Simt Multi and Legg Mason
-0.24 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Simt and Legg is -0.24. Overlapping area represents the amount of risk that can be diversified away by holding Simt Multi Asset Inflation and Legg Mason Bw in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Legg Mason Bw and Simt Multi 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 Simt Multi Asset Inflation are associated (or correlated) with Legg Mason. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Legg Mason Bw has no effect on the direction of Simt Multi i.e., Simt Multi and Legg Mason go up and down completely randomly.
Pair Corralation between Simt Multi and Legg Mason
Assuming the 90 days horizon Simt Multi is expected to generate 4.17 times less return on investment than Legg Mason. But when comparing it to its historical volatility, Simt Multi Asset Inflation is 2.91 times less risky than Legg Mason. It trades about 0.07 of its potential returns per unit of risk. Legg Mason Bw is currently generating about 0.1 of returns per unit of risk over similar time horizon. If you would invest 1,802 in Legg Mason Bw on September 12, 2024 and sell it today you would earn a total of 506.00 from holding Legg Mason Bw or generate 28.08% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Simt Multi Asset Inflation vs. Legg Mason Bw
Performance |
| Timeline |
| Simt Multi Asset |
| Legg Mason Bw |
Simt Multi and Legg Mason Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Simt Multi and Legg Mason
The main advantage of trading using opposite Simt Multi and Legg Mason positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Simt Multi position performs unexpectedly, Legg Mason 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 Legg Mason will offset losses from the drop in Legg Mason's long position.| Simt Multi vs. Capital Income Builder | Simt Multi vs. Capital Income Builder | Simt Multi vs. Capital Income Builder | Simt Multi vs. Capital Income Builder |
| Legg Mason vs. Simt Multi Asset Inflation | Legg Mason vs. Loomis Sayles Inflation | Legg Mason vs. Guggenheim Managed Futures | Legg Mason vs. Ab Bond Inflation |
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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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