Correlation Between Union Semiconductor and Xiangyang Automobile
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By analyzing existing cross correlation between Union Semiconductor Co and Xiangyang Automobile Bearing, you can compare the effects of market volatilities on Union Semiconductor and Xiangyang Automobile 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 Union Semiconductor with a short position of Xiangyang Automobile. Check out your portfolio center. Please also check ongoing floating volatility patterns of Union Semiconductor and Xiangyang Automobile.
Diversification Opportunities for Union Semiconductor and Xiangyang Automobile
0.82 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Union and Xiangyang is 0.82. Overlapping area represents the amount of risk that can be diversified away by holding Union Semiconductor Co and Xiangyang Automobile Bearing in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Xiangyang Automobile and Union Semiconductor 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 Union Semiconductor Co are associated (or correlated) with Xiangyang Automobile. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Xiangyang Automobile has no effect on the direction of Union Semiconductor i.e., Union Semiconductor and Xiangyang Automobile go up and down completely randomly.
Pair Corralation between Union Semiconductor and Xiangyang Automobile
Assuming the 90 days trading horizon Union Semiconductor is expected to generate 1.18 times less return on investment than Xiangyang Automobile. In addition to that, Union Semiconductor is 1.05 times more volatile than Xiangyang Automobile Bearing. It trades about 0.15 of its total potential returns per unit of risk. Xiangyang Automobile Bearing is currently generating about 0.19 per unit of volatility. If you would invest 452.00 in Xiangyang Automobile Bearing on September 10, 2024 and sell it today you would earn a total of 225.00 from holding Xiangyang Automobile Bearing or generate 49.78% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Union Semiconductor Co vs. Xiangyang Automobile Bearing
Performance |
Timeline |
Union Semiconductor |
Xiangyang Automobile |
Union Semiconductor and Xiangyang Automobile Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Union Semiconductor and Xiangyang Automobile
The main advantage of trading using opposite Union Semiconductor and Xiangyang Automobile positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Union Semiconductor position performs unexpectedly, Xiangyang Automobile 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 Xiangyang Automobile will offset losses from the drop in Xiangyang Automobile's long position.Union Semiconductor vs. Minmetals Capital Co | Union Semiconductor vs. Guangzhou Zhujiang Brewery | Union Semiconductor vs. Chengtun Mining Group | Union Semiconductor vs. Guangdong Jingyi Metal |
Xiangyang Automobile vs. Linewell Software Co | Xiangyang Automobile vs. Cofoe Medical Technology | Xiangyang Automobile vs. Fujian Rongji Software | Xiangyang Automobile vs. Maider Medical Industry |
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 Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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