Correlation Between Dow Jones and Covalon Technologies
Can any of the company-specific risk be diversified away by investing in both Dow Jones and Covalon Technologies 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 Dow Jones and Covalon Technologies into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Dow Jones Industrial and Covalon Technologies, you can compare the effects of market volatilities on Dow Jones and Covalon Technologies 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 Dow Jones with a short position of Covalon Technologies. Check out your portfolio center. Please also check ongoing floating volatility patterns of Dow Jones and Covalon Technologies.
Diversification Opportunities for Dow Jones and Covalon Technologies
0.55 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Dow and Covalon is 0.55. Overlapping area represents the amount of risk that can be diversified away by holding Dow Jones Industrial and Covalon Technologies in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Covalon Technologies and Dow Jones 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 Dow Jones Industrial are associated (or correlated) with Covalon Technologies. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Covalon Technologies has no effect on the direction of Dow Jones i.e., Dow Jones and Covalon Technologies go up and down completely randomly.
Pair Corralation between Dow Jones and Covalon Technologies
Assuming the 90 days trading horizon Dow Jones Industrial is expected to generate 0.23 times more return on investment than Covalon Technologies. However, Dow Jones Industrial is 4.3 times less risky than Covalon Technologies. It trades about -0.04 of its potential returns per unit of risk. Covalon Technologies is currently generating about -0.13 per unit of risk. If you would invest 4,257,373 in Dow Jones Industrial on December 29, 2024 and sell it today you would lose (98,983) from holding Dow Jones Industrial or give up 2.32% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 96.83% |
Values | Daily Returns |
Dow Jones Industrial vs. Covalon Technologies
Performance |
Timeline |
Dow Jones and Covalon Technologies Volatility Contrast
Predicted Return Density |
Returns |
Dow Jones Industrial
Pair trading matchups for Dow Jones
Covalon Technologies
Pair trading matchups for Covalon Technologies
Pair Trading with Dow Jones and Covalon Technologies
The main advantage of trading using opposite Dow Jones and Covalon Technologies positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dow Jones position performs unexpectedly, Covalon Technologies 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 Covalon Technologies will offset losses from the drop in Covalon Technologies' long position.Dow Jones vs. Perseus Mining Limited | Dow Jones vs. Falcon Metals Limited | Dow Jones vs. Broadstone Net Lease | Dow Jones vs. PennantPark Investment |
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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