Correlation Between Angel Oak and Leland Thomson
Can any of the company-specific risk be diversified away by investing in both Angel Oak and Leland Thomson 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 Angel Oak and Leland Thomson into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Angel Oak Multi Strategy and Leland Thomson Reuters, you can compare the effects of market volatilities on Angel Oak and Leland Thomson 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 Angel Oak with a short position of Leland Thomson. Check out your portfolio center. Please also check ongoing floating volatility patterns of Angel Oak and Leland Thomson.
Diversification Opportunities for Angel Oak and Leland Thomson
-0.46 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Angel and Leland is -0.46. Overlapping area represents the amount of risk that can be diversified away by holding Angel Oak Multi Strategy and Leland Thomson Reuters in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Leland Thomson Reuters and Angel Oak 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 Angel Oak Multi Strategy are associated (or correlated) with Leland Thomson. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Leland Thomson Reuters has no effect on the direction of Angel Oak i.e., Angel Oak and Leland Thomson go up and down completely randomly.
Pair Corralation between Angel Oak and Leland Thomson
Assuming the 90 days horizon Angel Oak is expected to generate 4.53 times less return on investment than Leland Thomson. But when comparing it to its historical volatility, Angel Oak Multi Strategy is 11.32 times less risky than Leland Thomson. It trades about 0.14 of its potential returns per unit of risk. Leland Thomson Reuters is currently generating about 0.06 of returns per unit of risk over similar time horizon. If you would invest 2,113 in Leland Thomson Reuters on September 30, 2024 and sell it today you would earn a total of 236.00 from holding Leland Thomson Reuters or generate 11.17% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Angel Oak Multi Strategy vs. Leland Thomson Reuters
Performance |
Timeline |
Angel Oak Multi |
Leland Thomson Reuters |
Angel Oak and Leland Thomson Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Angel Oak and Leland Thomson
The main advantage of trading using opposite Angel Oak and Leland Thomson positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Angel Oak position performs unexpectedly, Leland Thomson 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 Leland Thomson will offset losses from the drop in Leland Thomson's long position.Angel Oak vs. Gabelli Gold Fund | Angel Oak vs. Europac Gold Fund | Angel Oak vs. Gold And Precious | Angel Oak vs. Great West Goldman Sachs |
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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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