Correlation Between Kohls Corp and Allison Transmission
Can any of the company-specific risk be diversified away by investing in both Kohls Corp and Allison Transmission 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 Kohls Corp and Allison Transmission into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Kohls Corp and Allison Transmission Holdings, you can compare the effects of market volatilities on Kohls Corp and Allison Transmission 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 Kohls Corp with a short position of Allison Transmission. Check out your portfolio center. Please also check ongoing floating volatility patterns of Kohls Corp and Allison Transmission.
Diversification Opportunities for Kohls Corp and Allison Transmission
-0.67 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Kohls and Allison is -0.67. Overlapping area represents the amount of risk that can be diversified away by holding Kohls Corp and Allison Transmission Holdings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Allison Transmission and Kohls Corp 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 Kohls Corp are associated (or correlated) with Allison Transmission. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Allison Transmission has no effect on the direction of Kohls Corp i.e., Kohls Corp and Allison Transmission go up and down completely randomly.
Pair Corralation between Kohls Corp and Allison Transmission
Considering the 90-day investment horizon Kohls Corp is expected to under-perform the Allison Transmission. In addition to that, Kohls Corp is 2.04 times more volatile than Allison Transmission Holdings. It trades about -0.19 of its total potential returns per unit of risk. Allison Transmission Holdings is currently generating about 0.32 per unit of volatility. If you would invest 9,993 in Allison Transmission Holdings on August 30, 2024 and sell it today you would earn a total of 1,865 from holding Allison Transmission Holdings or generate 18.66% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Kohls Corp vs. Allison Transmission Holdings
Performance |
Timeline |
Kohls Corp |
Allison Transmission |
Kohls Corp and Allison Transmission Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Kohls Corp and Allison Transmission
The main advantage of trading using opposite Kohls Corp and Allison Transmission positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Kohls Corp position performs unexpectedly, Allison Transmission 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 Allison Transmission will offset losses from the drop in Allison Transmission's long position.Kohls Corp vs. Nordstrom | Kohls Corp vs. Dillards | Kohls Corp vs. Marks Spencer Group | Kohls Corp vs. Marks and Spencer |
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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 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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