Correlation Between Where Food and Nabors Industries
Can any of the company-specific risk be diversified away by investing in both Where Food and Nabors Industries 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 Where Food and Nabors Industries into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Where Food Comes and Nabors Industries, you can compare the effects of market volatilities on Where Food and Nabors Industries 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 Where Food with a short position of Nabors Industries. Check out your portfolio center. Please also check ongoing floating volatility patterns of Where Food and Nabors Industries.
Diversification Opportunities for Where Food and Nabors Industries
-0.74 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Where and Nabors is -0.74. Overlapping area represents the amount of risk that can be diversified away by holding Where Food Comes and Nabors Industries in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Nabors Industries and Where Food 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 Where Food Comes are associated (or correlated) with Nabors Industries. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Nabors Industries has no effect on the direction of Where Food i.e., Where Food and Nabors Industries go up and down completely randomly.
Pair Corralation between Where Food and Nabors Industries
Given the investment horizon of 90 days Where Food Comes is expected to generate 0.66 times more return on investment than Nabors Industries. However, Where Food Comes is 1.52 times less risky than Nabors Industries. It trades about 0.01 of its potential returns per unit of risk. Nabors Industries is currently generating about -0.04 per unit of risk. If you would invest 1,363 in Where Food Comes on October 13, 2024 and sell it today you would lose (89.00) from holding Where Food Comes or give up 6.53% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Where Food Comes vs. Nabors Industries
Performance |
Timeline |
Where Food Comes |
Nabors Industries |
Where Food and Nabors Industries Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Where Food and Nabors Industries
The main advantage of trading using opposite Where Food and Nabors Industries positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Where Food position performs unexpectedly, Nabors Industries 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 Industries will offset losses from the drop in Nabors Industries' long position.Where Food vs. Issuer Direct Corp | Where Food vs. Smith Midland Corp | Where Food vs. Bm Technologies | Where Food vs. 1StdibsCom |
Nabors Industries vs. Helmerich and Payne | Nabors Industries vs. Precision Drilling | Nabors Industries vs. Seadrill Limited | Nabors Industries vs. Borr Drilling |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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