Correlation Between NEW PACIFIC and Heidelberg Materials
Can any of the company-specific risk be diversified away by investing in both NEW PACIFIC and Heidelberg Materials 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 NEW PACIFIC and Heidelberg Materials into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NEW PACIFIC METALS and Heidelberg Materials AG, you can compare the effects of market volatilities on NEW PACIFIC and Heidelberg Materials 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 NEW PACIFIC with a short position of Heidelberg Materials. Check out your portfolio center. Please also check ongoing floating volatility patterns of NEW PACIFIC and Heidelberg Materials.
Diversification Opportunities for NEW PACIFIC and Heidelberg Materials
-0.46 | Correlation Coefficient |
Very good diversification
The 3 months correlation between NEW and Heidelberg is -0.46. Overlapping area represents the amount of risk that can be diversified away by holding NEW PACIFIC METALS and Heidelberg Materials AG in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Heidelberg Materials and NEW PACIFIC 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 NEW PACIFIC METALS are associated (or correlated) with Heidelberg Materials. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Heidelberg Materials has no effect on the direction of NEW PACIFIC i.e., NEW PACIFIC and Heidelberg Materials go up and down completely randomly.
Pair Corralation between NEW PACIFIC and Heidelberg Materials
Assuming the 90 days trading horizon NEW PACIFIC METALS is expected to under-perform the Heidelberg Materials. In addition to that, NEW PACIFIC is 4.42 times more volatile than Heidelberg Materials AG. It trades about -0.05 of its total potential returns per unit of risk. Heidelberg Materials AG is currently generating about 0.18 per unit of volatility. If you would invest 10,825 in Heidelberg Materials AG on October 7, 2024 and sell it today you would earn a total of 1,195 from holding Heidelberg Materials AG or generate 11.04% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
NEW PACIFIC METALS vs. Heidelberg Materials AG
Performance |
Timeline |
NEW PACIFIC METALS |
Heidelberg Materials |
NEW PACIFIC and Heidelberg Materials Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with NEW PACIFIC and Heidelberg Materials
The main advantage of trading using opposite NEW PACIFIC and Heidelberg Materials positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NEW PACIFIC position performs unexpectedly, Heidelberg Materials 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 Heidelberg Materials will offset losses from the drop in Heidelberg Materials' long position.NEW PACIFIC vs. THAI BEVERAGE | NEW PACIFIC vs. PURETECH HEALTH PLC | NEW PACIFIC vs. SAN MIGUEL BREWERY | NEW PACIFIC vs. Molson Coors Beverage |
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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 Portfolio Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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