Correlation Between Hochschild Mining and CNH Industrial
Can any of the company-specific risk be diversified away by investing in both Hochschild Mining and CNH Industrial 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 Hochschild Mining and CNH Industrial into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Hochschild Mining plc and CNH Industrial NV, you can compare the effects of market volatilities on Hochschild Mining and CNH Industrial 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 Hochschild Mining with a short position of CNH Industrial. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hochschild Mining and CNH Industrial.
Diversification Opportunities for Hochschild Mining and CNH Industrial
0.34 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Hochschild and CNH is 0.34. Overlapping area represents the amount of risk that can be diversified away by holding Hochschild Mining plc and CNH Industrial NV in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CNH Industrial NV and Hochschild Mining 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 Hochschild Mining plc are associated (or correlated) with CNH Industrial. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CNH Industrial NV has no effect on the direction of Hochschild Mining i.e., Hochschild Mining and CNH Industrial go up and down completely randomly.
Pair Corralation between Hochschild Mining and CNH Industrial
Assuming the 90 days trading horizon Hochschild Mining plc is expected to generate 0.76 times more return on investment than CNH Industrial. However, Hochschild Mining plc is 1.31 times less risky than CNH Industrial. It trades about 0.14 of its potential returns per unit of risk. CNH Industrial NV is currently generating about 0.03 per unit of risk. If you would invest 9,105 in Hochschild Mining plc on September 5, 2024 and sell it today you would earn a total of 13,395 from holding Hochschild Mining plc or generate 147.12% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 87.2% |
| Values | Daily Returns |
Hochschild Mining plc vs. CNH Industrial NV
Performance |
| Timeline |
| Hochschild Mining plc |
| CNH Industrial NV |
Hochschild Mining and CNH Industrial Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Hochschild Mining and CNH Industrial
The main advantage of trading using opposite Hochschild Mining and CNH Industrial positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hochschild Mining position performs unexpectedly, CNH Industrial 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 CNH Industrial will offset losses from the drop in CNH Industrial's long position.| Hochschild Mining vs. Givaudan SA | Hochschild Mining vs. Antofagasta PLC | Hochschild Mining vs. Atalaya Mining | Hochschild Mining vs. Ferrexpo PLC |
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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 Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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