Correlation Between Financial Industries and Legg Mason
Can any of the company-specific risk be diversified away by investing in both Financial Industries 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 Financial Industries and Legg Mason into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Financial Industries Fund and Legg Mason Partners, you can compare the effects of market volatilities on Financial Industries 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 Financial Industries with a short position of Legg Mason. Check out your portfolio center. Please also check ongoing floating volatility patterns of Financial Industries and Legg Mason.
Diversification Opportunities for Financial Industries and Legg Mason
0.64 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Financial and Legg is 0.64. Overlapping area represents the amount of risk that can be diversified away by holding Financial Industries Fund and Legg Mason Partners in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Legg Mason Partners and Financial Industries 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 Financial Industries Fund 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 Partners has no effect on the direction of Financial Industries i.e., Financial Industries and Legg Mason go up and down completely randomly.
Pair Corralation between Financial Industries and Legg Mason
Assuming the 90 days horizon Financial Industries Fund is expected to generate 1.15 times more return on investment than Legg Mason. However, Financial Industries is 1.15 times more volatile than Legg Mason Partners. It trades about 0.01 of its potential returns per unit of risk. Legg Mason Partners is currently generating about -0.09 per unit of risk. If you would invest 1,900 in Financial Industries Fund on October 24, 2024 and sell it today you would lose (2.00) from holding Financial Industries Fund or give up 0.11% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 98.33% |
Values | Daily Returns |
Financial Industries Fund vs. Legg Mason Partners
Performance |
Timeline |
Financial Industries |
Legg Mason Partners |
Financial Industries and Legg Mason Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Financial Industries and Legg Mason
The main advantage of trading using opposite Financial Industries and Legg Mason positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Financial Industries 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.Financial Industries vs. Maryland Tax Free Bond | Financial Industries vs. Bts Tactical Fixed | Financial Industries vs. Artisan High Income | Financial Industries vs. Blrc Sgy Mnp |
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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 Price Exposure Probability module to analyze equity upside and downside potential for a given time horizon across multiple markets.
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