Correlation Between Hochschild Mining and GlobalData PLC
Can any of the company-specific risk be diversified away by investing in both Hochschild Mining and GlobalData PLC 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 GlobalData PLC 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 GlobalData PLC, you can compare the effects of market volatilities on Hochschild Mining and GlobalData PLC 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 GlobalData PLC. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hochschild Mining and GlobalData PLC.
Diversification Opportunities for Hochschild Mining and GlobalData PLC
-0.89 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Hochschild and GlobalData is -0.89. Overlapping area represents the amount of risk that can be diversified away by holding Hochschild Mining plc and GlobalData PLC in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on GlobalData PLC 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 GlobalData PLC. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of GlobalData PLC has no effect on the direction of Hochschild Mining i.e., Hochschild Mining and GlobalData PLC go up and down completely randomly.
Pair Corralation between Hochschild Mining and GlobalData PLC
Assuming the 90 days trading horizon Hochschild Mining plc is expected to generate 1.66 times more return on investment than GlobalData PLC. However, Hochschild Mining is 1.66 times more volatile than GlobalData PLC. It trades about 0.05 of its potential returns per unit of risk. GlobalData PLC is currently generating about -0.12 per unit of risk. If you would invest 23,650 in Hochschild Mining plc on January 26, 2025 and sell it today you would earn a total of 3,230 from holding Hochschild Mining plc or generate 13.66% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Hochschild Mining plc vs. GlobalData PLC
Performance |
Timeline |
Hochschild Mining plc |
GlobalData PLC |
Hochschild Mining and GlobalData PLC Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Hochschild Mining and GlobalData PLC
The main advantage of trading using opposite Hochschild Mining and GlobalData PLC positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hochschild Mining position performs unexpectedly, GlobalData PLC 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 GlobalData PLC will offset losses from the drop in GlobalData PLC's long position.Hochschild Mining vs. Axway Software SA | Hochschild Mining vs. Aptitude Software Group | Hochschild Mining vs. Leroy Seafood Group | Hochschild Mining vs. Associated British Foods |
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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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