Correlation Between Super Energy and Dow Jones
Can any of the company-specific risk be diversified away by investing in both Super Energy 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 Super Energy and Dow Jones into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Super Energy and Dow Jones Industrial, you can compare the effects of market volatilities on Super Energy 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 Super Energy with a short position of Dow Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of Super Energy and Dow Jones.
Diversification Opportunities for Super Energy and Dow Jones
0.19 | Correlation Coefficient |
Average diversification
The 3 months correlation between Super and Dow is 0.19. Overlapping area represents the amount of risk that can be diversified away by holding Super Energy 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 Super Energy 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 Super Energy 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 Super Energy i.e., Super Energy and Dow Jones go up and down completely randomly.
Pair Corralation between Super Energy and Dow Jones
Assuming the 90 days trading horizon Super Energy is expected to generate 1.59 times less return on investment than Dow Jones. In addition to that, Super Energy is 3.83 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 0.21 per unit of volatility. If you would invest 4,075,575 in Dow Jones Industrial on September 5, 2024 and sell it today you would earn a total of 425,829 from holding Dow Jones Industrial or generate 10.45% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 96.88% |
Values | Daily Returns |
Super Energy vs. Dow Jones Industrial
Performance |
Timeline |
Super Energy and Dow Jones Volatility Contrast
Predicted Return Density |
Returns |
Super Energy
Pair trading matchups for Super Energy
Dow Jones Industrial
Pair trading matchups for Dow Jones
Pair Trading with Super Energy and Dow Jones
The main advantage of trading using opposite Super Energy and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Super Energy 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.Super Energy vs. Bangchak Public | Super Energy vs. Gulf Energy Development | Super Energy vs. Bangkok Expressway and | Super Energy vs. BGrimm Power Public |
Dow Jones vs. Shake Shack | Dow Jones vs. Artisan Partners Asset | Dow Jones vs. Dave Busters Entertainment | Dow Jones vs. Meli Hotels International |
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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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