Correlation Between Sinomach Automobile and Huasi Agricultural
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By analyzing existing cross correlation between Sinomach Automobile Co and Huasi Agricultural Development, you can compare the effects of market volatilities on Sinomach Automobile and Huasi 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 Sinomach Automobile with a short position of Huasi Agricultural. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sinomach Automobile and Huasi Agricultural.
Diversification Opportunities for Sinomach Automobile and Huasi Agricultural
0.62 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Sinomach and Huasi is 0.62. Overlapping area represents the amount of risk that can be diversified away by holding Sinomach Automobile Co and Huasi Agricultural Development in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Huasi Agricultural and Sinomach Automobile 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 Sinomach Automobile Co are associated (or correlated) with Huasi Agricultural. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Huasi Agricultural has no effect on the direction of Sinomach Automobile i.e., Sinomach Automobile and Huasi Agricultural go up and down completely randomly.
Pair Corralation between Sinomach Automobile and Huasi Agricultural
Assuming the 90 days trading horizon Sinomach Automobile is expected to generate 2.39 times less return on investment than Huasi Agricultural. But when comparing it to its historical volatility, Sinomach Automobile Co is 1.25 times less risky than Huasi Agricultural. It trades about 0.08 of its potential returns per unit of risk. Huasi Agricultural Development is currently generating about 0.15 of returns per unit of risk over similar time horizon. If you would invest 405.00 in Huasi Agricultural Development on December 2, 2024 and sell it today you would earn a total of 19.00 from holding Huasi Agricultural Development or generate 4.69% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Sinomach Automobile Co vs. Huasi Agricultural Development
Performance |
Timeline |
Sinomach Automobile |
Huasi Agricultural |
Sinomach Automobile and Huasi Agricultural Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Sinomach Automobile and Huasi Agricultural
The main advantage of trading using opposite Sinomach Automobile and Huasi Agricultural positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sinomach Automobile position performs unexpectedly, Huasi 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 Huasi Agricultural will offset losses from the drop in Huasi Agricultural's long position.Sinomach Automobile vs. Huawen Media Investment | Sinomach Automobile vs. Zhejiang Daily Media | Sinomach Automobile vs. Hengdian Entertainment Co | Sinomach Automobile vs. Guilin Seamild Foods |
Huasi Agricultural vs. China Life Insurance | Huasi Agricultural vs. Maxvision Technology Corp | Huasi Agricultural vs. Digiwin Software Co | Huasi Agricultural vs. Bangyan Technology 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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