Correlation Between Columbus McKinnon and Dow Jones
Can any of the company-specific risk be diversified away by investing in both Columbus McKinnon 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 Columbus McKinnon and Dow Jones into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Columbus McKinnon and Dow Jones Industrial, you can compare the effects of market volatilities on Columbus McKinnon 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 Columbus McKinnon with a short position of Dow Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of Columbus McKinnon and Dow Jones.
Diversification Opportunities for Columbus McKinnon and Dow Jones
0.81 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Columbus and Dow is 0.81. Overlapping area represents the amount of risk that can be diversified away by holding Columbus McKinnon 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 Columbus McKinnon 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 Columbus McKinnon 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 Columbus McKinnon i.e., Columbus McKinnon and Dow Jones go up and down completely randomly.
Pair Corralation between Columbus McKinnon and Dow Jones
Given the investment horizon of 90 days Columbus McKinnon is expected to generate 2.64 times more return on investment than Dow Jones. However, Columbus McKinnon is 2.64 times more volatile than Dow Jones Industrial. It trades about 0.23 of its potential returns per unit of risk. Dow Jones Industrial is currently generating about 0.15 per unit of risk. If you would invest 3,270 in Columbus McKinnon on August 24, 2024 and sell it today you would earn a total of 444.00 from holding Columbus McKinnon or generate 13.58% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Columbus McKinnon vs. Dow Jones Industrial
Performance |
Timeline |
Columbus McKinnon and Dow Jones Volatility Contrast
Predicted Return Density |
Returns |
Columbus McKinnon
Pair trading matchups for Columbus McKinnon
Dow Jones Industrial
Pair trading matchups for Dow Jones
Pair Trading with Columbus McKinnon and Dow Jones
The main advantage of trading using opposite Columbus McKinnon and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Columbus McKinnon 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.Columbus McKinnon vs. Lindsay | Columbus McKinnon vs. Astec Industries | Columbus McKinnon vs. Shyft Group | Columbus McKinnon vs. AGCO Corporation |
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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 Technical Analysis module to check basic technical indicators and analysis based on most latest market data.
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