Correlation Between Transamerica Asset and Legg Mason
Can any of the company-specific risk be diversified away by investing in both Transamerica Asset 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 Transamerica Asset and Legg Mason into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Transamerica Asset Allocation and Legg Mason Partners, you can compare the effects of market volatilities on Transamerica Asset 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 Transamerica Asset with a short position of Legg Mason. Check out your portfolio center. Please also check ongoing floating volatility patterns of Transamerica Asset and Legg Mason.
Diversification Opportunities for Transamerica Asset and Legg Mason
0.92 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Transamerica and Legg is 0.92. Overlapping area represents the amount of risk that can be diversified away by holding Transamerica Asset Allocation 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 Transamerica Asset 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 Transamerica Asset Allocation 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 Transamerica Asset i.e., Transamerica Asset and Legg Mason go up and down completely randomly.
Pair Corralation between Transamerica Asset and Legg Mason
Assuming the 90 days horizon Transamerica Asset Allocation is expected to generate 1.27 times more return on investment than Legg Mason. However, Transamerica Asset is 1.27 times more volatile than Legg Mason Partners. It trades about 0.16 of its potential returns per unit of risk. Legg Mason Partners is currently generating about 0.17 per unit of risk. If you would invest 1,332 in Transamerica Asset Allocation on September 4, 2024 and sell it today you would earn a total of 68.00 from holding Transamerica Asset Allocation or generate 5.11% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Transamerica Asset Allocation vs. Legg Mason Partners
Performance |
Timeline |
Transamerica Asset |
Legg Mason Partners |
Transamerica Asset and Legg Mason Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Transamerica Asset and Legg Mason
The main advantage of trading using opposite Transamerica Asset and Legg Mason positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Transamerica Asset 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.Transamerica Asset vs. 361 Global Longshort | Transamerica Asset vs. Barings Global Floating | Transamerica Asset vs. Commonwealth Global Fund | Transamerica Asset vs. Ab Global Bond |
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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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