Correlation Between Xiangyang Automobile and Betta Pharmaceuticals
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By analyzing existing cross correlation between Xiangyang Automobile Bearing and Betta Pharmaceuticals Co, you can compare the effects of market volatilities on Xiangyang Automobile and Betta Pharmaceuticals 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 Betta Pharmaceuticals. Check out your portfolio center. Please also check ongoing floating volatility patterns of Xiangyang Automobile and Betta Pharmaceuticals.
Diversification Opportunities for Xiangyang Automobile and Betta Pharmaceuticals
0.84 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Xiangyang and Betta is 0.84. Overlapping area represents the amount of risk that can be diversified away by holding Xiangyang Automobile Bearing and Betta Pharmaceuticals Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Betta Pharmaceuticals 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 Betta Pharmaceuticals. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Betta Pharmaceuticals has no effect on the direction of Xiangyang Automobile i.e., Xiangyang Automobile and Betta Pharmaceuticals go up and down completely randomly.
Pair Corralation between Xiangyang Automobile and Betta Pharmaceuticals
Assuming the 90 days trading horizon Xiangyang Automobile Bearing is expected to generate 1.2 times more return on investment than Betta Pharmaceuticals. However, Xiangyang Automobile is 1.2 times more volatile than Betta Pharmaceuticals Co. It trades about 0.03 of its potential returns per unit of risk. Betta Pharmaceuticals Co is currently generating about 0.02 per unit of risk. If you would invest 662.00 in Xiangyang Automobile Bearing on September 14, 2024 and sell it today you would earn a total of 71.00 from holding Xiangyang Automobile Bearing or generate 10.73% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 99.58% |
| Values | Daily Returns |
Xiangyang Automobile Bearing vs. Betta Pharmaceuticals Co
Performance |
| Timeline |
| Xiangyang Automobile |
| Betta Pharmaceuticals |
Xiangyang Automobile and Betta Pharmaceuticals Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Xiangyang Automobile and Betta Pharmaceuticals
The main advantage of trading using opposite Xiangyang Automobile and Betta Pharmaceuticals positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Xiangyang Automobile position performs unexpectedly, Betta Pharmaceuticals 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 Betta Pharmaceuticals will offset losses from the drop in Betta Pharmaceuticals' long position.| Xiangyang Automobile vs. BeiGene | Xiangyang Automobile vs. Kweichow Moutai Co | Xiangyang Automobile vs. Beijing Roborock Technology | Xiangyang Automobile vs. G bits Network Technology |
| Betta Pharmaceuticals vs. BeiGene | Betta Pharmaceuticals vs. Kweichow Moutai Co | Betta Pharmaceuticals vs. Beijing Roborock Technology | Betta Pharmaceuticals vs. G bits Network Technology |
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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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