Correlation Between JinkoSolar Holding and Jacquet Metal
Can any of the company-specific risk be diversified away by investing in both JinkoSolar Holding and Jacquet Metal 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 JinkoSolar Holding and Jacquet Metal into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between JinkoSolar Holding Co and Jacquet Metal Service, you can compare the effects of market volatilities on JinkoSolar Holding and Jacquet Metal 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 JinkoSolar Holding with a short position of Jacquet Metal. Check out your portfolio center. Please also check ongoing floating volatility patterns of JinkoSolar Holding and Jacquet Metal.
Diversification Opportunities for JinkoSolar Holding and Jacquet Metal
0.44 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between JinkoSolar and Jacquet is 0.44. Overlapping area represents the amount of risk that can be diversified away by holding JinkoSolar Holding Co and Jacquet Metal Service in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Jacquet Metal Service and JinkoSolar Holding 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 JinkoSolar Holding Co are associated (or correlated) with Jacquet Metal. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Jacquet Metal Service has no effect on the direction of JinkoSolar Holding i.e., JinkoSolar Holding and Jacquet Metal go up and down completely randomly.
Pair Corralation between JinkoSolar Holding and Jacquet Metal
Assuming the 90 days trading horizon JinkoSolar Holding Co is expected to generate 2.91 times more return on investment than Jacquet Metal. However, JinkoSolar Holding is 2.91 times more volatile than Jacquet Metal Service. It trades about 0.13 of its potential returns per unit of risk. Jacquet Metal Service is currently generating about 0.3 per unit of risk. If you would invest 2,060 in JinkoSolar Holding Co on September 22, 2024 and sell it today you would earn a total of 260.00 from holding JinkoSolar Holding Co or generate 12.62% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 95.65% |
Values | Daily Returns |
JinkoSolar Holding Co vs. Jacquet Metal Service
Performance |
Timeline |
JinkoSolar Holding |
Jacquet Metal Service |
JinkoSolar Holding and Jacquet Metal Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with JinkoSolar Holding and Jacquet Metal
The main advantage of trading using opposite JinkoSolar Holding and Jacquet Metal positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if JinkoSolar Holding position performs unexpectedly, Jacquet Metal 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 Jacquet Metal will offset losses from the drop in Jacquet Metal's long position.JinkoSolar Holding vs. Hyster Yale Materials Handling | JinkoSolar Holding vs. LION ONE METALS | JinkoSolar Holding vs. DISTRICT METALS | JinkoSolar Holding vs. Materialise NV |
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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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