Correlation Between Nasdaq 100 and Oppenheimer Rochester
Can any of the company-specific risk be diversified away by investing in both Nasdaq 100 and Oppenheimer Rochester 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 Nasdaq 100 and Oppenheimer Rochester into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Nasdaq 100 Index Fund and Oppenheimer Rochester, you can compare the effects of market volatilities on Nasdaq 100 and Oppenheimer Rochester 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 Nasdaq 100 with a short position of Oppenheimer Rochester. Check out your portfolio center. Please also check ongoing floating volatility patterns of Nasdaq 100 and Oppenheimer Rochester.
Diversification Opportunities for Nasdaq 100 and Oppenheimer Rochester
-0.32 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Nasdaq and Oppenheimer is -0.32. Overlapping area represents the amount of risk that can be diversified away by holding Nasdaq 100 Index Fund and Oppenheimer Rochester in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Oppenheimer Rochester and Nasdaq 100 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 Nasdaq 100 Index Fund are associated (or correlated) with Oppenheimer Rochester. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Oppenheimer Rochester has no effect on the direction of Nasdaq 100 i.e., Nasdaq 100 and Oppenheimer Rochester go up and down completely randomly.
Pair Corralation between Nasdaq 100 and Oppenheimer Rochester
Assuming the 90 days horizon Nasdaq 100 Index Fund is expected to generate 1.99 times more return on investment than Oppenheimer Rochester. However, Nasdaq 100 is 1.99 times more volatile than Oppenheimer Rochester. It trades about 0.25 of its potential returns per unit of risk. Oppenheimer Rochester is currently generating about 0.16 per unit of risk. If you would invest 4,998 in Nasdaq 100 Index Fund on September 1, 2024 and sell it today you would earn a total of 264.00 from holding Nasdaq 100 Index Fund or generate 5.28% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 95.45% |
| Values | Daily Returns |
Nasdaq 100 Index Fund vs. Oppenheimer Rochester
Performance |
| Timeline |
| Nasdaq 100 Index |
| Oppenheimer Rochester |
Nasdaq 100 and Oppenheimer Rochester Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Nasdaq 100 and Oppenheimer Rochester
The main advantage of trading using opposite Nasdaq 100 and Oppenheimer Rochester positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Nasdaq 100 position performs unexpectedly, Oppenheimer Rochester 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 Rochester will offset losses from the drop in Oppenheimer Rochester's long position.| Nasdaq 100 vs. Alliancebernstein National Municipal | Nasdaq 100 vs. Nuveen Arizona Municipal | Nasdaq 100 vs. Bbh Intermediate Municipal | Nasdaq 100 vs. Old Westbury Municipal |
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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