Correlation Between Yanzhou Coal and Peabody Energy
Can any of the company-specific risk be diversified away by investing in both Yanzhou Coal and Peabody Energy 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 Yanzhou Coal and Peabody Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Yanzhou Coal Mining and Peabody Energy, you can compare the effects of market volatilities on Yanzhou Coal and Peabody Energy 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 Yanzhou Coal with a short position of Peabody Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of Yanzhou Coal and Peabody Energy.
Diversification Opportunities for Yanzhou Coal and Peabody Energy
0.61 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Yanzhou and Peabody is 0.61. Overlapping area represents the amount of risk that can be diversified away by holding Yanzhou Coal Mining and Peabody Energy in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Peabody Energy and Yanzhou Coal 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 Yanzhou Coal Mining are associated (or correlated) with Peabody Energy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Peabody Energy has no effect on the direction of Yanzhou Coal i.e., Yanzhou Coal and Peabody Energy go up and down completely randomly.
Pair Corralation between Yanzhou Coal and Peabody Energy
Assuming the 90 days trading horizon Yanzhou Coal Mining is expected to generate 0.9 times more return on investment than Peabody Energy. However, Yanzhou Coal Mining is 1.11 times less risky than Peabody Energy. It trades about 0.01 of its potential returns per unit of risk. Peabody Energy is currently generating about -0.37 per unit of risk. If you would invest 112.00 in Yanzhou Coal Mining on September 18, 2024 and sell it today you would earn a total of 0.00 from holding Yanzhou Coal Mining or generate 0.0% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 95.45% |
Values | Daily Returns |
Yanzhou Coal Mining vs. Peabody Energy
Performance |
Timeline |
Yanzhou Coal Mining |
Peabody Energy |
Yanzhou Coal and Peabody Energy Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Yanzhou Coal and Peabody Energy
The main advantage of trading using opposite Yanzhou Coal and Peabody Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Yanzhou Coal position performs unexpectedly, Peabody Energy 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 Peabody Energy will offset losses from the drop in Peabody Energy's long position.Yanzhou Coal vs. China Shenhua Energy | Yanzhou Coal vs. PT Bayan Resources | Yanzhou Coal vs. PT Adaro Energy | Yanzhou Coal vs. Yancoal Australia |
Peabody Energy vs. China Shenhua Energy | Peabody Energy vs. PT Bayan Resources | Peabody Energy vs. Yanzhou Coal Mining | Peabody Energy vs. PT Adaro Energy |
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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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