Correlation Between Oil Refineries and Dow Jones
Can any of the company-specific risk be diversified away by investing in both Oil Refineries and Dow Jones 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 Oil Refineries and Dow Jones into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Oil Refineries and Dow Jones Industrial, you can compare the effects of market volatilities on Oil Refineries and Dow Jones 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 Oil Refineries with a short position of Dow Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of Oil Refineries and Dow Jones.
Diversification Opportunities for Oil Refineries and Dow Jones
0.56 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Oil and Dow is 0.56. Overlapping area represents the amount of risk that can be diversified away by holding Oil Refineries and Dow Jones Industrial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dow Jones Industrial and Oil Refineries 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 Oil Refineries are associated (or correlated) with Dow Jones. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dow Jones Industrial has no effect on the direction of Oil Refineries i.e., Oil Refineries and Dow Jones go up and down completely randomly.
Pair Corralation between Oil Refineries and Dow Jones
Assuming the 90 days trading horizon Oil Refineries is expected to under-perform the Dow Jones. In addition to that, Oil Refineries is 3.45 times more volatile than Dow Jones Industrial. It trades about -0.03 of its total potential returns per unit of risk. Dow Jones Industrial is currently generating about 0.12 per unit of volatility. If you would invest 3,640,493 in Dow Jones Industrial on September 4, 2024 and sell it today you would earn a total of 837,707 from holding Dow Jones Industrial or generate 23.01% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 77.24% |
| Values | Daily Returns |
Oil Refineries vs. Dow Jones Industrial
Performance |
| Timeline |
Oil Refineries and Dow Jones Volatility Contrast
Predicted Return Density |
| Returns |
Oil Refineries
Pair trading matchups for Oil Refineries
Dow Jones Industrial
Pair trading matchups for Dow Jones
Pair Trading with Oil Refineries and Dow Jones
The main advantage of trading using opposite Oil Refineries and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Oil Refineries position performs unexpectedly, Dow Jones 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 Dow Jones will offset losses from the drop in Dow Jones' long position.| Oil Refineries vs. Delek Group | Oil Refineries vs. Bank Leumi Le Israel | Oil Refineries vs. ICL Israel Chemicals | Oil Refineries vs. Bank Hapoalim |
| Dow Jones vs. Gentex | Dow Jones vs. American Axle Manufacturing | Dow Jones vs. Pearson PLC ADR | Dow Jones vs. Marine Products |
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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