Correlation Between Oppenheimer Senior and Lord Abbett
Can any of the company-specific risk be diversified away by investing in both Oppenheimer Senior and Lord Abbett 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 Oppenheimer Senior and Lord Abbett into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Oppenheimer Senior Floating and Lord Abbett Floating, you can compare the effects of market volatilities on Oppenheimer Senior and Lord Abbett 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 Oppenheimer Senior with a short position of Lord Abbett. Check out your portfolio center. Please also check ongoing floating volatility patterns of Oppenheimer Senior and Lord Abbett.
Diversification Opportunities for Oppenheimer Senior and Lord Abbett
0.94 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Oppenheimer and Lord is 0.94. Overlapping area represents the amount of risk that can be diversified away by holding Oppenheimer Senior Floating and Lord Abbett Floating in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Lord Abbett Floating and Oppenheimer Senior 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 Oppenheimer Senior Floating are associated (or correlated) with Lord Abbett. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Lord Abbett Floating has no effect on the direction of Oppenheimer Senior i.e., Oppenheimer Senior and Lord Abbett go up and down completely randomly.
Pair Corralation between Oppenheimer Senior and Lord Abbett
Assuming the 90 days horizon Oppenheimer Senior Floating is expected to under-perform the Lord Abbett. In addition to that, Oppenheimer Senior is 1.09 times more volatile than Lord Abbett Floating. It trades about -0.08 of its total potential returns per unit of risk. Lord Abbett Floating is currently generating about 0.07 per unit of volatility. If you would invest 818.00 in Lord Abbett Floating on September 1, 2024 and sell it today you would earn a total of 1.00 from holding Lord Abbett Floating or generate 0.12% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Oppenheimer Senior Floating vs. Lord Abbett Floating
Performance |
Timeline |
Oppenheimer Senior |
Lord Abbett Floating |
Oppenheimer Senior and Lord Abbett Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Oppenheimer Senior and Lord Abbett
The main advantage of trading using opposite Oppenheimer Senior and Lord Abbett positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Oppenheimer Senior position performs unexpectedly, Lord Abbett 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 Lord Abbett will offset losses from the drop in Lord Abbett's long position.Oppenheimer Senior vs. Technology Ultrasector Profund | Oppenheimer Senior vs. Goldman Sachs Technology | Oppenheimer Senior vs. Dreyfus Technology Growth | Oppenheimer Senior vs. Towpath Technology |
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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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