Correlation Between Shanghai V-Test and Xingguang Agricultural
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By analyzing existing cross correlation between Shanghai V Test Semiconductor and Xingguang Agricultural Mach, you can compare the effects of market volatilities on Shanghai V-Test and Xingguang Agricultural 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 Shanghai V-Test with a short position of Xingguang Agricultural. Check out your portfolio center. Please also check ongoing floating volatility patterns of Shanghai V-Test and Xingguang Agricultural.
Diversification Opportunities for Shanghai V-Test and Xingguang Agricultural
-0.13 | Correlation Coefficient |
Good diversification
The 3 months correlation between Shanghai and Xingguang is -0.13. Overlapping area represents the amount of risk that can be diversified away by holding Shanghai V Test Semiconductor and Xingguang Agricultural Mach in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Xingguang Agricultural and Shanghai V-Test 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 Shanghai V Test Semiconductor are associated (or correlated) with Xingguang Agricultural. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Xingguang Agricultural has no effect on the direction of Shanghai V-Test i.e., Shanghai V-Test and Xingguang Agricultural go up and down completely randomly.
Pair Corralation between Shanghai V-Test and Xingguang Agricultural
Assuming the 90 days trading horizon Shanghai V Test Semiconductor is expected to generate 1.25 times more return on investment than Xingguang Agricultural. However, Shanghai V-Test is 1.25 times more volatile than Xingguang Agricultural Mach. It trades about 0.27 of its potential returns per unit of risk. Xingguang Agricultural Mach is currently generating about -0.34 per unit of risk. If you would invest 5,753 in Shanghai V Test Semiconductor on November 3, 2024 and sell it today you would earn a total of 1,337 from holding Shanghai V Test Semiconductor or generate 23.24% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Shanghai V Test Semiconductor vs. Xingguang Agricultural Mach
Performance |
| Timeline |
| Shanghai V Test |
| Xingguang Agricultural |
Shanghai V-Test and Xingguang Agricultural Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Shanghai V-Test and Xingguang Agricultural
The main advantage of trading using opposite Shanghai V-Test and Xingguang Agricultural positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Shanghai V-Test position performs unexpectedly, Xingguang Agricultural 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 Xingguang Agricultural will offset losses from the drop in Xingguang Agricultural's long position.| Shanghai V-Test vs. Industrial and Commercial | Shanghai V-Test vs. Kweichow Moutai Co | Shanghai V-Test vs. Agricultural Bank of | Shanghai V-Test vs. China Mobile Limited |
| Xingguang Agricultural vs. Industrial and Commercial | Xingguang Agricultural vs. Kweichow Moutai Co | Xingguang Agricultural vs. Agricultural Bank of | Xingguang Agricultural vs. China Mobile Limited |
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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.
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