Correlation Between Dicker Data and Dow Jones
Can any of the company-specific risk be diversified away by investing in both Dicker Data 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 Dicker Data and Dow Jones into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Dicker Data and Dow Jones Industrial, you can compare the effects of market volatilities on Dicker Data 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 Dicker Data with a short position of Dow Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of Dicker Data and Dow Jones.
Diversification Opportunities for Dicker Data and Dow Jones
0.47 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Dicker and Dow is 0.47. Overlapping area represents the amount of risk that can be diversified away by holding Dicker Data 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 Dicker Data 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 Dicker Data 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 Dicker Data i.e., Dicker Data and Dow Jones go up and down completely randomly.
Pair Corralation between Dicker Data and Dow Jones
Assuming the 90 days trading horizon Dicker Data is expected to generate 1.26 times less return on investment than Dow Jones. In addition to that, Dicker Data is 2.67 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 0.09 per unit of volatility. If you would invest 3,266,184 in Dow Jones Industrial on November 20, 2024 and sell it today you would earn a total of 1,188,424 from holding Dow Jones Industrial or generate 36.39% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 99.4% |
Values | Daily Returns |
Dicker Data vs. Dow Jones Industrial
Performance |
Timeline |
Dicker Data and Dow Jones Volatility Contrast
Predicted Return Density |
Returns |
Dicker Data
Pair trading matchups for Dicker Data
Dow Jones Industrial
Pair trading matchups for Dow Jones
Pair Trading with Dicker Data and Dow Jones
The main advantage of trading using opposite Dicker Data and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dicker Data 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.Dicker Data vs. Cleanaway Waste Management | Dicker Data vs. Mount Gibson Iron | Dicker Data vs. Clime Investment Management | Dicker Data vs. Autosports Group |
Dow Jones vs. Topbuild Corp | Dow Jones vs. Parker Hannifin | Dow Jones vs. CNA Financial | Dow Jones vs. Valmont Industries |
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 Portfolio Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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