Correlation Between ULTRA CLEAN and Aluminumof China
Can any of the company-specific risk be diversified away by investing in both ULTRA CLEAN and Aluminumof China at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining ULTRA CLEAN and Aluminumof China into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between ULTRA CLEAN HLDGS and Aluminum of, you can compare the effects of market volatilities on ULTRA CLEAN and Aluminumof China 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 ULTRA CLEAN with a short position of Aluminumof China. Check out your portfolio center. Please also check ongoing floating volatility patterns of ULTRA CLEAN and Aluminumof China.
Diversification Opportunities for ULTRA CLEAN and Aluminumof China
0.69 | Correlation Coefficient |
Poor diversification
The 3 months correlation between ULTRA and Aluminumof is 0.69. Overlapping area represents the amount of risk that can be diversified away by holding ULTRA CLEAN HLDGS and Aluminum of in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Aluminumof China and ULTRA CLEAN 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 ULTRA CLEAN HLDGS are associated (or correlated) with Aluminumof China. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Aluminumof China has no effect on the direction of ULTRA CLEAN i.e., ULTRA CLEAN and Aluminumof China go up and down completely randomly.
Pair Corralation between ULTRA CLEAN and Aluminumof China
Assuming the 90 days trading horizon ULTRA CLEAN HLDGS is expected to generate 0.58 times more return on investment than Aluminumof China. However, ULTRA CLEAN HLDGS is 1.74 times less risky than Aluminumof China. It trades about 0.31 of its potential returns per unit of risk. Aluminum of is currently generating about 0.1 per unit of risk. If you would invest 3,060 in ULTRA CLEAN HLDGS on September 1, 2024 and sell it today you would earn a total of 560.00 from holding ULTRA CLEAN HLDGS or generate 18.3% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
ULTRA CLEAN HLDGS vs. Aluminum of
Performance |
| Timeline |
| ULTRA CLEAN HLDGS |
| Aluminumof China |
ULTRA CLEAN and Aluminumof China Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with ULTRA CLEAN and Aluminumof China
The main advantage of trading using opposite ULTRA CLEAN and Aluminumof China positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if ULTRA CLEAN position performs unexpectedly, Aluminumof China 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 Aluminumof China will offset losses from the drop in Aluminumof China's long position.| ULTRA CLEAN vs. DEVRY EDUCATION GRP | ULTRA CLEAN vs. WILLIS LEASE FIN | ULTRA CLEAN vs. G8 EDUCATION | ULTRA CLEAN vs. Grand Canyon Education |
| Aluminumof China vs. PLAYTIKA HOLDING DL 01 | Aluminumof China vs. COSMOSTEEL HLDGS | Aluminumof China vs. Daido Steel Co | Aluminumof China vs. BLUESCOPE STEEL |
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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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