Correlation Between Dow Jones and Oppenheimer Main
Can any of the company-specific risk be diversified away by investing in both Dow Jones and Oppenheimer Main 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 Dow Jones and Oppenheimer Main into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Dow Jones Industrial and Oppenheimer Main Street, you can compare the effects of market volatilities on Dow Jones and Oppenheimer Main 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 Dow Jones with a short position of Oppenheimer Main. Check out your portfolio center. Please also check ongoing floating volatility patterns of Dow Jones and Oppenheimer Main.
Diversification Opportunities for Dow Jones and Oppenheimer Main
0.88 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Dow and Oppenheimer is 0.88. Overlapping area represents the amount of risk that can be diversified away by holding Dow Jones Industrial and Oppenheimer Main Street in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Oppenheimer Main Street and Dow Jones 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 Dow Jones Industrial are associated (or correlated) with Oppenheimer Main. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Oppenheimer Main Street has no effect on the direction of Dow Jones i.e., Dow Jones and Oppenheimer Main go up and down completely randomly.
Pair Corralation between Dow Jones and Oppenheimer Main
Assuming the 90 days trading horizon Dow Jones Industrial is expected to generate 0.55 times more return on investment than Oppenheimer Main. However, Dow Jones Industrial is 1.82 times less risky than Oppenheimer Main. It trades about 0.04 of its potential returns per unit of risk. Oppenheimer Main Street is currently generating about -0.05 per unit of risk. If you would invest 4,212,465 in Dow Jones Industrial on September 22, 2024 and sell it today you would earn a total of 71,561 from holding Dow Jones Industrial or generate 1.7% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Dow Jones Industrial vs. Oppenheimer Main Street
Performance |
Timeline |
Dow Jones and Oppenheimer Main Volatility Contrast
Predicted Return Density |
Returns |
Dow Jones Industrial
Pair trading matchups for Dow Jones
Oppenheimer Main Street
Pair trading matchups for Oppenheimer Main
Pair Trading with Dow Jones and Oppenheimer Main
The main advantage of trading using opposite Dow Jones and Oppenheimer Main positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dow Jones position performs unexpectedly, Oppenheimer Main 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 Oppenheimer Main will offset losses from the drop in Oppenheimer Main's long position.Dow Jones vs. Hurco Companies | Dow Jones vs. Sabre Corpo | Dow Jones vs. Glacier Bancorp | Dow Jones vs. Barings BDC |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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