Correlation Between United States and GOLD ROAD
Can any of the company-specific risk be diversified away by investing in both United States and GOLD ROAD 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 United States and GOLD ROAD into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between United States Steel and GOLD ROAD RES, you can compare the effects of market volatilities on United States and GOLD ROAD 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 United States with a short position of GOLD ROAD. Check out your portfolio center. Please also check ongoing floating volatility patterns of United States and GOLD ROAD.
Diversification Opportunities for United States and GOLD ROAD
-0.37 | Correlation Coefficient |
Very good diversification
The 3 months correlation between United and GOLD is -0.37. Overlapping area represents the amount of risk that can be diversified away by holding United States Steel and GOLD ROAD RES in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on GOLD ROAD RES and United States 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 United States Steel are associated (or correlated) with GOLD ROAD. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of GOLD ROAD RES has no effect on the direction of United States i.e., United States and GOLD ROAD go up and down completely randomly.
Pair Corralation between United States and GOLD ROAD
Assuming the 90 days trading horizon United States Steel is expected to generate 3.53 times more return on investment than GOLD ROAD. However, United States is 3.53 times more volatile than GOLD ROAD RES. It trades about 0.25 of its potential returns per unit of risk. GOLD ROAD RES is currently generating about 0.74 per unit of risk. If you would invest 2,976 in United States Steel on October 20, 2024 and sell it today you would earn a total of 550.00 from holding United States Steel or generate 18.48% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
United States Steel vs. GOLD ROAD RES
Performance |
| Timeline |
| United States Steel |
| GOLD ROAD RES |
United States and GOLD ROAD Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with United States and GOLD ROAD
The main advantage of trading using opposite United States and GOLD ROAD positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if United States position performs unexpectedly, GOLD ROAD 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 GOLD ROAD will offset losses from the drop in GOLD ROAD's long position.| United States vs. Webster Financial | United States vs. Erste Group Bank | United States vs. Algonquin Power Utilities | United States vs. CDN IMPERIAL BANK |
| GOLD ROAD vs. United States Steel | GOLD ROAD vs. Kingdee International Software | GOLD ROAD vs. Easy Software AG | GOLD ROAD vs. Nippon Steel |
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 Technical Analysis module to check basic technical indicators and analysis based on most latest market data.
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