Correlation Between Oppenheimer Holdings and Houlihan Lokey
Can any of the company-specific risk be diversified away by investing in both Oppenheimer Holdings and Houlihan Lokey 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 Holdings and Houlihan Lokey into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Oppenheimer Holdings and Houlihan Lokey, you can compare the effects of market volatilities on Oppenheimer Holdings and Houlihan Lokey 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 Holdings with a short position of Houlihan Lokey. Check out your portfolio center. Please also check ongoing floating volatility patterns of Oppenheimer Holdings and Houlihan Lokey.
Diversification Opportunities for Oppenheimer Holdings and Houlihan Lokey
0.78 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Oppenheimer and Houlihan is 0.78. Overlapping area represents the amount of risk that can be diversified away by holding Oppenheimer Holdings and Houlihan Lokey in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Houlihan Lokey and Oppenheimer Holdings 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 Holdings are associated (or correlated) with Houlihan Lokey. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Houlihan Lokey has no effect on the direction of Oppenheimer Holdings i.e., Oppenheimer Holdings and Houlihan Lokey go up and down completely randomly.
Pair Corralation between Oppenheimer Holdings and Houlihan Lokey
Considering the 90-day investment horizon Oppenheimer Holdings is expected to generate 1.16 times less return on investment than Houlihan Lokey. In addition to that, Oppenheimer Holdings is 1.15 times more volatile than Houlihan Lokey. It trades about 0.14 of its total potential returns per unit of risk. Houlihan Lokey is currently generating about 0.19 per unit of volatility. If you would invest 15,145 in Houlihan Lokey on August 31, 2024 and sell it today you would earn a total of 3,598 from holding Houlihan Lokey or generate 23.76% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Oppenheimer Holdings vs. Houlihan Lokey
Performance |
Timeline |
Oppenheimer Holdings |
Houlihan Lokey |
Oppenheimer Holdings and Houlihan Lokey Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Oppenheimer Holdings and Houlihan Lokey
The main advantage of trading using opposite Oppenheimer Holdings and Houlihan Lokey positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Oppenheimer Holdings position performs unexpectedly, Houlihan Lokey 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 Houlihan Lokey will offset losses from the drop in Houlihan Lokey's long position.Oppenheimer Holdings vs. PJT Partners | Oppenheimer Holdings vs. Houlihan Lokey | Oppenheimer Holdings vs. Stifel Financial | Oppenheimer Holdings vs. Evercore Partners |
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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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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