Correlation Between Dow Jones and Nabors Energy
Can any of the company-specific risk be diversified away by investing in both Dow Jones and Nabors Energy 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 Nabors Energy 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 Nabors Energy Transition, you can compare the effects of market volatilities on Dow Jones and Nabors Energy 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 Nabors Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Dow Jones and Nabors Energy.
Diversification Opportunities for Dow Jones and Nabors Energy
0.64 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Dow and Nabors is 0.64. Overlapping area represents the amount of risk that can be diversified away by holding Dow Jones Industrial and Nabors Energy Transition in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Nabors Energy Transition 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 Nabors Energy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Nabors Energy Transition has no effect on the direction of Dow Jones i.e., Dow Jones and Nabors Energy go up and down completely randomly.
Pair Corralation between Dow Jones and Nabors Energy
Assuming the 90 days trading horizon Dow Jones is expected to generate 80.79 times less return on investment than Nabors Energy. But when comparing it to its historical volatility, Dow Jones Industrial is 24.46 times less risky than Nabors Energy. It trades about 0.07 of its potential returns per unit of risk. Nabors Energy Transition is currently generating about 0.24 of returns per unit of risk over similar time horizon. If you would invest 11.00 in Nabors Energy Transition on September 18, 2024 and sell it today you would earn a total of 6.00 from holding Nabors Energy Transition or generate 54.55% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 95.0% |
Values | Daily Returns |
Dow Jones Industrial vs. Nabors Energy Transition
Performance |
Timeline |
Dow Jones and Nabors Energy Volatility Contrast
Predicted Return Density |
Returns |
Dow Jones Industrial
Pair trading matchups for Dow Jones
Nabors Energy Transition
Pair trading matchups for Nabors Energy
Pair Trading with Dow Jones and Nabors Energy
The main advantage of trading using opposite Dow Jones and Nabors Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dow Jones position performs unexpectedly, Nabors Energy 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 Nabors Energy will offset losses from the drop in Nabors Energy's long position.Dow Jones vs. Commonwealth Bank of | Dow Jones vs. AmTrust Financial Services | Dow Jones vs. Forsys Metals Corp | Dow Jones vs. Juniata Valley Financial |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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