Correlation Between Applied Finance and Western Asset
Can any of the company-specific risk be diversified away by investing in both Applied Finance and Western Asset 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 Applied Finance and Western Asset into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Applied Finance Explorer and Western Asset E, you can compare the effects of market volatilities on Applied Finance and Western Asset 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 Applied Finance with a short position of Western Asset. Check out your portfolio center. Please also check ongoing floating volatility patterns of Applied Finance and Western Asset.
Diversification Opportunities for Applied Finance and Western Asset
-0.64 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Applied and Western is -0.64. Overlapping area represents the amount of risk that can be diversified away by holding Applied Finance Explorer and Western Asset E in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Western Asset E and Applied Finance 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 Applied Finance Explorer are associated (or correlated) with Western Asset. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Western Asset E has no effect on the direction of Applied Finance i.e., Applied Finance and Western Asset go up and down completely randomly.
Pair Corralation between Applied Finance and Western Asset
Assuming the 90 days horizon Applied Finance Explorer is expected to generate 3.5 times more return on investment than Western Asset. However, Applied Finance is 3.5 times more volatile than Western Asset E. It trades about 0.06 of its potential returns per unit of risk. Western Asset E is currently generating about 0.03 per unit of risk. If you would invest 1,764 in Applied Finance Explorer on August 31, 2024 and sell it today you would earn a total of 664.00 from holding Applied Finance Explorer or generate 37.64% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 99.73% |
Values | Daily Returns |
Applied Finance Explorer vs. Western Asset E
Performance |
Timeline |
Applied Finance Explorer |
Western Asset E |
Applied Finance and Western Asset Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Applied Finance and Western Asset
The main advantage of trading using opposite Applied Finance and Western Asset positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Applied Finance position performs unexpectedly, Western Asset 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 Western Asset will offset losses from the drop in Western Asset's long position.Applied Finance vs. Vanguard Small Cap Value | Applied Finance vs. Vanguard Small Cap Value | Applied Finance vs. Us Targeted Value | Applied Finance vs. Undiscovered Managers Behavioral |
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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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