Correlation Between Inspur Software and Shantui Construction
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By analyzing existing cross correlation between Inspur Software Co and Shantui Construction Machinery, you can compare the effects of market volatilities on Inspur Software and Shantui Construction 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 Inspur Software with a short position of Shantui Construction. Check out your portfolio center. Please also check ongoing floating volatility patterns of Inspur Software and Shantui Construction.
Diversification Opportunities for Inspur Software and Shantui Construction
0.09 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Inspur and Shantui is 0.09. Overlapping area represents the amount of risk that can be diversified away by holding Inspur Software Co and Shantui Construction Machinery in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Shantui Construction and Inspur Software 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 Inspur Software Co are associated (or correlated) with Shantui Construction. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Shantui Construction has no effect on the direction of Inspur Software i.e., Inspur Software and Shantui Construction go up and down completely randomly.
Pair Corralation between Inspur Software and Shantui Construction
Assuming the 90 days trading horizon Inspur Software is expected to generate 28.01 times less return on investment than Shantui Construction. In addition to that, Inspur Software is 1.01 times more volatile than Shantui Construction Machinery. It trades about 0.0 of its total potential returns per unit of risk. Shantui Construction Machinery is currently generating about 0.07 per unit of volatility. If you would invest 424.00 in Shantui Construction Machinery on October 16, 2024 and sell it today you would earn a total of 517.00 from holding Shantui Construction Machinery or generate 121.93% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Inspur Software Co vs. Shantui Construction Machinery
Performance |
| Timeline |
| Inspur Software |
| Shantui Construction |
Inspur Software and Shantui Construction Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Inspur Software and Shantui Construction
The main advantage of trading using opposite Inspur Software and Shantui Construction positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Inspur Software position performs unexpectedly, Shantui Construction 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 Shantui Construction will offset losses from the drop in Shantui Construction's long position.| Inspur Software vs. Unisplendour Corp | Inspur Software vs. Kontour Medical Technology | Inspur Software vs. Allmed Medical Products | Inspur Software vs. Jiangsu Financial Leasing |
| Shantui Construction vs. Inspur Software Co | Shantui Construction vs. Advanced Technology Materials | Shantui Construction vs. Guangzhou Tinci Materials | Shantui Construction vs. Western Metal Materials |
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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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