Correlation Between Kaiser Aluminum and Constellium
Can any of the company-specific risk be diversified away by investing in both Kaiser Aluminum and Constellium 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 Kaiser Aluminum and Constellium into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Kaiser Aluminum and Constellium Nv, you can compare the effects of market volatilities on Kaiser Aluminum and Constellium 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 Kaiser Aluminum with a short position of Constellium. Check out your portfolio center. Please also check ongoing floating volatility patterns of Kaiser Aluminum and Constellium.
Diversification Opportunities for Kaiser Aluminum and Constellium
0.67 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Kaiser and Constellium is 0.67. Overlapping area represents the amount of risk that can be diversified away by holding Kaiser Aluminum and Constellium Nv in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Constellium Nv and Kaiser Aluminum 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 Kaiser Aluminum are associated (or correlated) with Constellium. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Constellium Nv has no effect on the direction of Kaiser Aluminum i.e., Kaiser Aluminum and Constellium go up and down completely randomly.
Pair Corralation between Kaiser Aluminum and Constellium
Given the investment horizon of 90 days Kaiser Aluminum is expected to generate 1.23 times more return on investment than Constellium. However, Kaiser Aluminum is 1.23 times more volatile than Constellium Nv. It trades about 0.13 of its potential returns per unit of risk. Constellium Nv is currently generating about 0.12 per unit of risk. If you would invest 7,588 in Kaiser Aluminum on August 31, 2025 and sell it today you would earn a total of 1,993 from holding Kaiser Aluminum or generate 26.27% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Kaiser Aluminum vs. Constellium Nv
Performance |
| Timeline |
| Kaiser Aluminum |
| Constellium Nv |
Kaiser Aluminum and Constellium Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Kaiser Aluminum and Constellium
The main advantage of trading using opposite Kaiser Aluminum and Constellium positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Kaiser Aluminum position performs unexpectedly, Constellium 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 Constellium will offset losses from the drop in Constellium's long position.| Kaiser Aluminum vs. Braemar Hotels Resorts | Kaiser Aluminum vs. Grupo Carso SAB | Kaiser Aluminum vs. Oasis Hotel Resort | Kaiser Aluminum vs. American Hotel Income |
| Constellium vs. ProUroCare Medical | Constellium vs. Nates Food Co | Constellium vs. Kelvin Medical | Constellium vs. Seneca Foods |
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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