Correlation Between NEXE Innovations and Dow Jones
Can any of the company-specific risk be diversified away by investing in both NEXE Innovations 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 NEXE Innovations and Dow Jones into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NEXE Innovations and Dow Jones Industrial, you can compare the effects of market volatilities on NEXE Innovations 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 NEXE Innovations with a short position of Dow Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of NEXE Innovations and Dow Jones.
Diversification Opportunities for NEXE Innovations and Dow Jones
0.26 | Correlation Coefficient |
Modest diversification
The 3 months correlation between NEXE and Dow is 0.26. Overlapping area represents the amount of risk that can be diversified away by holding NEXE Innovations 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 NEXE Innovations 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 NEXE Innovations 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 NEXE Innovations i.e., NEXE Innovations and Dow Jones go up and down completely randomly.
Pair Corralation between NEXE Innovations and Dow Jones
Assuming the 90 days horizon NEXE Innovations is expected to under-perform the Dow Jones. In addition to that, NEXE Innovations is 5.28 times more volatile than Dow Jones Industrial. It trades about -0.08 of its total potential returns per unit of risk. Dow Jones Industrial is currently generating about -0.08 per unit of volatility. If you would invest 4,372,993 in Dow Jones Industrial on October 7, 2024 and sell it today you would lose (99,780) from holding Dow Jones Industrial or give up 2.28% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 97.62% |
Values | Daily Returns |
NEXE Innovations vs. Dow Jones Industrial
Performance |
Timeline |
NEXE Innovations and Dow Jones Volatility Contrast
Predicted Return Density |
Returns |
NEXE Innovations
Pair trading matchups for NEXE Innovations
Dow Jones Industrial
Pair trading matchups for Dow Jones
Pair Trading with NEXE Innovations and Dow Jones
The main advantage of trading using opposite NEXE Innovations and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NEXE Innovations 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.NEXE Innovations vs. Imaflex | NEXE Innovations vs. Karat Packaging | NEXE Innovations vs. DSS Inc | NEXE Innovations vs. Myers Industries |
Dow Jones vs. Evertz Technologies Limited | Dow Jones vs. Amkor Technology | Dow Jones vs. Plexus Corp | Dow Jones vs. Valneva SE ADR |
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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