Correlation Between Hochschild Mining and Huaneng Power
Can any of the company-specific risk be diversified away by investing in both Hochschild Mining and Huaneng Power 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 Huaneng Power 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 Huaneng Power International, you can compare the effects of market volatilities on Hochschild Mining and Huaneng Power 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 Huaneng Power. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hochschild Mining and Huaneng Power.
Diversification Opportunities for Hochschild Mining and Huaneng Power
-0.5 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Hochschild and Huaneng is -0.5. Overlapping area represents the amount of risk that can be diversified away by holding Hochschild Mining plc and Huaneng Power International in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Huaneng Power Intern 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 Huaneng Power. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Huaneng Power Intern has no effect on the direction of Hochschild Mining i.e., Hochschild Mining and Huaneng Power go up and down completely randomly.
Pair Corralation between Hochschild Mining and Huaneng Power
Assuming the 90 days horizon Hochschild Mining plc is expected to generate 0.75 times more return on investment than Huaneng Power. However, Hochschild Mining plc is 1.33 times less risky than Huaneng Power. It trades about 0.13 of its potential returns per unit of risk. Huaneng Power International is currently generating about 0.05 per unit of risk. If you would invest 108.00 in Hochschild Mining plc on October 9, 2024 and sell it today you would earn a total of 164.00 from holding Hochschild Mining plc or generate 151.85% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 99.6% |
Values | Daily Returns |
Hochschild Mining plc vs. Huaneng Power International
Performance |
Timeline |
Hochschild Mining plc |
Huaneng Power Intern |
Hochschild Mining and Huaneng Power Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Hochschild Mining and Huaneng Power
The main advantage of trading using opposite Hochschild Mining and Huaneng Power positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hochschild Mining position performs unexpectedly, Huaneng Power 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 Huaneng Power will offset losses from the drop in Huaneng Power's long position.Hochschild Mining vs. China Communications Services | Hochschild Mining vs. Ribbon Communications | Hochschild Mining vs. CeoTronics AG | Hochschild Mining vs. CITIC Telecom International |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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