Correlation Between Ganfeng Lithium and PT Barito
Can any of the company-specific risk be diversified away by investing in both Ganfeng Lithium and PT Barito 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 Ganfeng Lithium and PT Barito into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ganfeng Lithium Co and PT Barito Pacific, you can compare the effects of market volatilities on Ganfeng Lithium and PT Barito 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 Ganfeng Lithium with a short position of PT Barito. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ganfeng Lithium and PT Barito.
Diversification Opportunities for Ganfeng Lithium and PT Barito
-0.71 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Ganfeng and OB8 is -0.71. Overlapping area represents the amount of risk that can be diversified away by holding Ganfeng Lithium Co and PT Barito Pacific in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on PT Barito Pacific and Ganfeng Lithium 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 Ganfeng Lithium Co are associated (or correlated) with PT Barito. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of PT Barito Pacific has no effect on the direction of Ganfeng Lithium i.e., Ganfeng Lithium and PT Barito go up and down completely randomly.
Pair Corralation between Ganfeng Lithium and PT Barito
Assuming the 90 days trading horizon Ganfeng Lithium Co is expected to generate 1.09 times more return on investment than PT Barito. However, Ganfeng Lithium is 1.09 times more volatile than PT Barito Pacific. It trades about 0.11 of its potential returns per unit of risk. PT Barito Pacific is currently generating about 0.0 per unit of risk. If you would invest 161.00 in Ganfeng Lithium Co on August 28, 2024 and sell it today you would earn a total of 149.00 from holding Ganfeng Lithium Co or generate 92.55% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Ganfeng Lithium Co vs. PT Barito Pacific
Performance |
Timeline |
Ganfeng Lithium |
PT Barito Pacific |
Ganfeng Lithium and PT Barito Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Ganfeng Lithium and PT Barito
The main advantage of trading using opposite Ganfeng Lithium and PT Barito positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ganfeng Lithium position performs unexpectedly, PT Barito 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 PT Barito will offset losses from the drop in PT Barito's long position.Ganfeng Lithium vs. Superior Plus Corp | Ganfeng Lithium vs. NMI Holdings | Ganfeng Lithium vs. Origin Agritech | Ganfeng Lithium vs. SIVERS SEMICONDUCTORS AB |
PT Barito vs. Superior Plus Corp | PT Barito vs. NMI Holdings | PT Barito vs. Origin Agritech | PT Barito vs. SIVERS SEMICONDUCTORS AB |
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 Valuation module to check real value of public entities based on technical and fundamental data.
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