Correlation Between Alfa Laval and Mitsubishi Heavy
Can any of the company-specific risk be diversified away by investing in both Alfa Laval and Mitsubishi Heavy 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 Alfa Laval and Mitsubishi Heavy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Alfa Laval AB and Mitsubishi Heavy Industries, you can compare the effects of market volatilities on Alfa Laval and Mitsubishi Heavy 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 Alfa Laval with a short position of Mitsubishi Heavy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Alfa Laval and Mitsubishi Heavy.
Diversification Opportunities for Alfa Laval and Mitsubishi Heavy
0.62 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Alfa and Mitsubishi is 0.62. Overlapping area represents the amount of risk that can be diversified away by holding Alfa Laval AB and Mitsubishi Heavy Industries in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mitsubishi Heavy Ind and Alfa Laval 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 Alfa Laval AB are associated (or correlated) with Mitsubishi Heavy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mitsubishi Heavy Ind has no effect on the direction of Alfa Laval i.e., Alfa Laval and Mitsubishi Heavy go up and down completely randomly.
Pair Corralation between Alfa Laval and Mitsubishi Heavy
Assuming the 90 days horizon Alfa Laval is expected to generate 4.47 times less return on investment than Mitsubishi Heavy. But when comparing it to its historical volatility, Alfa Laval AB is 2.75 times less risky than Mitsubishi Heavy. It trades about 0.09 of its potential returns per unit of risk. Mitsubishi Heavy Industries is currently generating about 0.15 of returns per unit of risk over similar time horizon. If you would invest 1,426 in Mitsubishi Heavy Industries on December 21, 2024 and sell it today you would earn a total of 521.00 from holding Mitsubishi Heavy Industries or generate 36.54% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 98.33% |
Values | Daily Returns |
Alfa Laval AB vs. Mitsubishi Heavy Industries
Performance |
Timeline |
Alfa Laval AB |
Mitsubishi Heavy Ind |
Alfa Laval and Mitsubishi Heavy Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Alfa Laval and Mitsubishi Heavy
The main advantage of trading using opposite Alfa Laval and Mitsubishi Heavy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Alfa Laval position performs unexpectedly, Mitsubishi Heavy 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 Mitsubishi Heavy will offset losses from the drop in Mitsubishi Heavy's long position.Alfa Laval vs. Aumann AG | Alfa Laval vs. Alfa Laval AB | Alfa Laval vs. Arista Power | Alfa Laval vs. Atlas Copco AB |
Mitsubishi Heavy vs. Kawasaki Heavy Industries | Mitsubishi Heavy vs. Mitsubishi Electric Corp | Mitsubishi Heavy vs. Mitsubishi Corp | Mitsubishi Heavy vs. Marubeni Corp 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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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