Correlation Between Fulin Plastic and Shinkong Synthetic
Can any of the company-specific risk be diversified away by investing in both Fulin Plastic and Shinkong Synthetic 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 Fulin Plastic and Shinkong Synthetic into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Fulin Plastic Industry and Shinkong Synthetic Fiber, you can compare the effects of market volatilities on Fulin Plastic and Shinkong Synthetic 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 Fulin Plastic with a short position of Shinkong Synthetic. Check out your portfolio center. Please also check ongoing floating volatility patterns of Fulin Plastic and Shinkong Synthetic.
Diversification Opportunities for Fulin Plastic and Shinkong Synthetic
-0.1 | Correlation Coefficient |
Good diversification
The 3 months correlation between Fulin and Shinkong is -0.1. Overlapping area represents the amount of risk that can be diversified away by holding Fulin Plastic Industry and Shinkong Synthetic Fiber in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Shinkong Synthetic Fiber and Fulin Plastic 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 Fulin Plastic Industry are associated (or correlated) with Shinkong Synthetic. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Shinkong Synthetic Fiber has no effect on the direction of Fulin Plastic i.e., Fulin Plastic and Shinkong Synthetic go up and down completely randomly.
Pair Corralation between Fulin Plastic and Shinkong Synthetic
Assuming the 90 days trading horizon Fulin Plastic Industry is expected to generate 0.88 times more return on investment than Shinkong Synthetic. However, Fulin Plastic Industry is 1.14 times less risky than Shinkong Synthetic. It trades about 0.07 of its potential returns per unit of risk. Shinkong Synthetic Fiber is currently generating about 0.03 per unit of risk. If you would invest 6,730 in Fulin Plastic Industry on October 22, 2024 and sell it today you would earn a total of 60.00 from holding Fulin Plastic Industry or generate 0.89% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Fulin Plastic Industry vs. Shinkong Synthetic Fiber
Performance |
Timeline |
Fulin Plastic Industry |
Shinkong Synthetic Fiber |
Fulin Plastic and Shinkong Synthetic Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Fulin Plastic and Shinkong Synthetic
The main advantage of trading using opposite Fulin Plastic and Shinkong Synthetic positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Fulin Plastic position performs unexpectedly, Shinkong Synthetic 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 Shinkong Synthetic will offset losses from the drop in Shinkong Synthetic's long position.Fulin Plastic vs. Tah Hsin Industrial | Fulin Plastic vs. Universal | Fulin Plastic vs. Taita Chemical Co | Fulin Plastic vs. San Fang Chemical |
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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 Competition Analyzer module to analyze and compare many basic indicators for a group of related or unrelated entities.
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