Correlation Between Zhangjiagang Freetrade and Cansino Biologics
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By analyzing existing cross correlation between Zhangjiagang Freetrade Science and Cansino Biologics, you can compare the effects of market volatilities on Zhangjiagang Freetrade and Cansino Biologics 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 Zhangjiagang Freetrade with a short position of Cansino Biologics. Check out your portfolio center. Please also check ongoing floating volatility patterns of Zhangjiagang Freetrade and Cansino Biologics.
Diversification Opportunities for Zhangjiagang Freetrade and Cansino Biologics
0.78 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Zhangjiagang and Cansino is 0.78. Overlapping area represents the amount of risk that can be diversified away by holding Zhangjiagang Freetrade Science and Cansino Biologics in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Cansino Biologics and Zhangjiagang Freetrade 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 Zhangjiagang Freetrade Science are associated (or correlated) with Cansino Biologics. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Cansino Biologics has no effect on the direction of Zhangjiagang Freetrade i.e., Zhangjiagang Freetrade and Cansino Biologics go up and down completely randomly.
Pair Corralation between Zhangjiagang Freetrade and Cansino Biologics
Assuming the 90 days trading horizon Zhangjiagang Freetrade Science is expected to generate 1.08 times more return on investment than Cansino Biologics. However, Zhangjiagang Freetrade is 1.08 times more volatile than Cansino Biologics. It trades about -0.09 of its potential returns per unit of risk. Cansino Biologics is currently generating about -0.15 per unit of risk. If you would invest 383.00 in Zhangjiagang Freetrade Science on October 30, 2024 and sell it today you would lose (35.00) from holding Zhangjiagang Freetrade Science or give up 9.14% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Zhangjiagang Freetrade Science vs. Cansino Biologics
Performance |
| Timeline |
| Zhangjiagang Freetrade |
| Cansino Biologics |
Zhangjiagang Freetrade and Cansino Biologics Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Zhangjiagang Freetrade and Cansino Biologics
The main advantage of trading using opposite Zhangjiagang Freetrade and Cansino Biologics positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Zhangjiagang Freetrade position performs unexpectedly, Cansino Biologics 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 Cansino Biologics will offset losses from the drop in Cansino Biologics' long position.| Zhangjiagang Freetrade vs. Ping An Insurance | Zhangjiagang Freetrade vs. Agricultural Bank of | Zhangjiagang Freetrade vs. Guosheng Financial Holding | Zhangjiagang Freetrade vs. Bank of Suzhou |
| Cansino Biologics vs. Zhongyin Babi Food | Cansino Biologics vs. Zhejiang Construction Investment | Cansino Biologics vs. Guilin Seamild Foods | Cansino Biologics vs. Tsingtao Brewery Co |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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