Correlation Between Mitsui Mining and Zhaojin Mining
Can any of the company-specific risk be diversified away by investing in both Mitsui Mining and Zhaojin Mining 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 Mitsui Mining and Zhaojin Mining into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mitsui Mining Smelting and Zhaojin Mining Industry, you can compare the effects of market volatilities on Mitsui Mining and Zhaojin Mining 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 Mitsui Mining with a short position of Zhaojin Mining. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mitsui Mining and Zhaojin Mining.
Diversification Opportunities for Mitsui Mining and Zhaojin Mining
0.48 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Mitsui and Zhaojin is 0.48. Overlapping area represents the amount of risk that can be diversified away by holding Mitsui Mining Smelting and Zhaojin Mining Industry in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Zhaojin Mining Industry and Mitsui 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 Mitsui Mining Smelting are associated (or correlated) with Zhaojin Mining. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Zhaojin Mining Industry has no effect on the direction of Mitsui Mining i.e., Mitsui Mining and Zhaojin Mining go up and down completely randomly.
Pair Corralation between Mitsui Mining and Zhaojin Mining
Assuming the 90 days horizon Mitsui Mining is expected to generate 1.5 times less return on investment than Zhaojin Mining. But when comparing it to its historical volatility, Mitsui Mining Smelting is 1.64 times less risky than Zhaojin Mining. It trades about 0.03 of its potential returns per unit of risk. Zhaojin Mining Industry is currently generating about 0.03 of returns per unit of risk over similar time horizon. If you would invest 105.00 in Zhaojin Mining Industry on October 4, 2024 and sell it today you would earn a total of 22.00 from holding Zhaojin Mining Industry or generate 20.95% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Mitsui Mining Smelting vs. Zhaojin Mining Industry
Performance |
Timeline |
Mitsui Mining Smelting |
Zhaojin Mining Industry |
Mitsui Mining and Zhaojin Mining Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Mitsui Mining and Zhaojin Mining
The main advantage of trading using opposite Mitsui Mining and Zhaojin Mining positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mitsui Mining position performs unexpectedly, Zhaojin Mining 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 Zhaojin Mining will offset losses from the drop in Zhaojin Mining's long position.Mitsui Mining vs. Constellation Software | Mitsui Mining vs. Jacquet Metal Service | Mitsui Mining vs. SIMS METAL MGT | Mitsui Mining vs. ATOSS SOFTWARE |
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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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