Correlation Between Xiangyang Automobile and Aofu Environmental
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By analyzing existing cross correlation between Xiangyang Automobile Bearing and Aofu Environmental Technology, you can compare the effects of market volatilities on Xiangyang Automobile and Aofu Environmental 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 Xiangyang Automobile with a short position of Aofu Environmental. Check out your portfolio center. Please also check ongoing floating volatility patterns of Xiangyang Automobile and Aofu Environmental.
Diversification Opportunities for Xiangyang Automobile and Aofu Environmental
0.73 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Xiangyang and Aofu is 0.73. Overlapping area represents the amount of risk that can be diversified away by holding Xiangyang Automobile Bearing and Aofu Environmental Technology in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Aofu Environmental and Xiangyang 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 Xiangyang Automobile Bearing are associated (or correlated) with Aofu Environmental. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Aofu Environmental has no effect on the direction of Xiangyang Automobile i.e., Xiangyang Automobile and Aofu Environmental go up and down completely randomly.
Pair Corralation between Xiangyang Automobile and Aofu Environmental
Assuming the 90 days trading horizon Xiangyang Automobile Bearing is expected to generate 1.53 times more return on investment than Aofu Environmental. However, Xiangyang Automobile is 1.53 times more volatile than Aofu Environmental Technology. It trades about 0.14 of its potential returns per unit of risk. Aofu Environmental Technology is currently generating about -0.02 per unit of risk. If you would invest 564.00 in Xiangyang Automobile Bearing on October 1, 2024 and sell it today you would earn a total of 144.00 from holding Xiangyang Automobile Bearing or generate 25.53% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Xiangyang Automobile Bearing vs. Aofu Environmental Technology
Performance |
Timeline |
Xiangyang Automobile |
Aofu Environmental |
Xiangyang Automobile and Aofu Environmental Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Xiangyang Automobile and Aofu Environmental
The main advantage of trading using opposite Xiangyang Automobile and Aofu Environmental positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Xiangyang Automobile position performs unexpectedly, Aofu Environmental 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 Aofu Environmental will offset losses from the drop in Aofu Environmental's long position.Xiangyang Automobile vs. Great Sun Foods Co | Xiangyang Automobile vs. Tongyu Communication | Xiangyang Automobile vs. Songz Automobile Air | Xiangyang Automobile vs. Haima Automobile Group |
Aofu Environmental vs. Zijin Mining Group | Aofu Environmental vs. Baoshan Iron Steel | Aofu Environmental vs. Shandong Gold Mining | Aofu Environmental vs. Rongsheng Petrochemical 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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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