Correlation Between NOV and Schlumberger
Can any of the company-specific risk be diversified away by investing in both NOV and Schlumberger 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 NOV and Schlumberger into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NOV Inc and Schlumberger NV, you can compare the effects of market volatilities on NOV and Schlumberger 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 NOV with a short position of Schlumberger. Check out your portfolio center. Please also check ongoing floating volatility patterns of NOV and Schlumberger.
Diversification Opportunities for NOV and Schlumberger
0.71 | Correlation Coefficient |
Poor diversification
The 3 months correlation between NOV and Schlumberger is 0.71. Overlapping area represents the amount of risk that can be diversified away by holding NOV Inc and Schlumberger NV in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Schlumberger NV and NOV 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 NOV Inc are associated (or correlated) with Schlumberger. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Schlumberger NV has no effect on the direction of NOV i.e., NOV and Schlumberger go up and down completely randomly.
Pair Corralation between NOV and Schlumberger
Considering the 90-day investment horizon NOV Inc is expected to generate 1.14 times more return on investment than Schlumberger. However, NOV is 1.14 times more volatile than Schlumberger NV. It trades about -0.03 of its potential returns per unit of risk. Schlumberger NV is currently generating about -0.38 per unit of risk. If you would invest 1,905 in NOV Inc on January 26, 2024 and sell it today you would lose (22.00) from holding NOV Inc or give up 1.15% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
NOV Inc vs. Schlumberger NV
Performance |
Timeline |
NOV Inc |
Schlumberger NV |
NOV and Schlumberger Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with NOV and Schlumberger
The main advantage of trading using opposite NOV and Schlumberger positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NOV position performs unexpectedly, Schlumberger 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 Schlumberger will offset losses from the drop in Schlumberger's long position.The idea behind NOV Inc and Schlumberger NV pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.Schlumberger vs. Enerflex | Schlumberger vs. Dril Quip | Schlumberger vs. Forum Energy Technologies | Schlumberger vs. Archrock |
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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