Correlation Between Guangzhou Automobile and Guangzhou Jointas
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By analyzing existing cross correlation between Guangzhou Automobile Group and Guangzhou Jointas Chemical, you can compare the effects of market volatilities on Guangzhou Automobile and Guangzhou Jointas 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 Guangzhou Automobile with a short position of Guangzhou Jointas. Check out your portfolio center. Please also check ongoing floating volatility patterns of Guangzhou Automobile and Guangzhou Jointas.
Diversification Opportunities for Guangzhou Automobile and Guangzhou Jointas
0.95 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Guangzhou and Guangzhou is 0.95. Overlapping area represents the amount of risk that can be diversified away by holding Guangzhou Automobile Group and Guangzhou Jointas Chemical in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Guangzhou Jointas and Guangzhou 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 Guangzhou Automobile Group are associated (or correlated) with Guangzhou Jointas. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Guangzhou Jointas has no effect on the direction of Guangzhou Automobile i.e., Guangzhou Automobile and Guangzhou Jointas go up and down completely randomly.
Pair Corralation between Guangzhou Automobile and Guangzhou Jointas
Assuming the 90 days trading horizon Guangzhou Automobile is expected to generate 5.25 times less return on investment than Guangzhou Jointas. But when comparing it to its historical volatility, Guangzhou Automobile Group is 1.31 times less risky than Guangzhou Jointas. It trades about 0.01 of its potential returns per unit of risk. Guangzhou Jointas Chemical is currently generating about 0.05 of returns per unit of risk over similar time horizon. If you would invest 479.00 in Guangzhou Jointas Chemical on August 31, 2024 and sell it today you would earn a total of 70.00 from holding Guangzhou Jointas Chemical or generate 14.61% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Guangzhou Automobile Group vs. Guangzhou Jointas Chemical
Performance |
| Timeline |
| Guangzhou Automobile |
| Guangzhou Jointas |
Guangzhou Automobile and Guangzhou Jointas Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Guangzhou Automobile and Guangzhou Jointas
The main advantage of trading using opposite Guangzhou Automobile and Guangzhou Jointas positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Guangzhou Automobile position performs unexpectedly, Guangzhou Jointas 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 Guangzhou Jointas will offset losses from the drop in Guangzhou Jointas' long position.| Guangzhou Automobile vs. China State Construction | Guangzhou Automobile vs. China Merchants Shekou | Guangzhou Automobile vs. Huafa Industrial Co | Guangzhou Automobile vs. China International Capital |
| Guangzhou Jointas vs. Jiangxi Naipu Mining | Guangzhou Jointas vs. Chenzhou Jingui Silver | Guangzhou Jointas vs. JCHX Mining Management | Guangzhou Jointas vs. Sinofibers 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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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