Correlation Between Hangzhou Gaoxin and Shanghai Material
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By analyzing existing cross correlation between Hangzhou Gaoxin Rubber and Shanghai Material Trading, you can compare the effects of market volatilities on Hangzhou Gaoxin and Shanghai Material 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 Hangzhou Gaoxin with a short position of Shanghai Material. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hangzhou Gaoxin and Shanghai Material.
Diversification Opportunities for Hangzhou Gaoxin and Shanghai Material
0.85 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Hangzhou and Shanghai is 0.85. Overlapping area represents the amount of risk that can be diversified away by holding Hangzhou Gaoxin Rubber and Shanghai Material Trading in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Shanghai Material Trading and Hangzhou Gaoxin 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 Hangzhou Gaoxin Rubber are associated (or correlated) with Shanghai Material. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Shanghai Material Trading has no effect on the direction of Hangzhou Gaoxin i.e., Hangzhou Gaoxin and Shanghai Material go up and down completely randomly.
Pair Corralation between Hangzhou Gaoxin and Shanghai Material
Assuming the 90 days trading horizon Hangzhou Gaoxin Rubber is expected to under-perform the Shanghai Material. But the stock apears to be less risky and, when comparing its historical volatility, Hangzhou Gaoxin Rubber is 2.22 times less risky than Shanghai Material. The stock trades about -0.04 of its potential returns per unit of risk. The Shanghai Material Trading is currently generating about 0.18 of returns per unit of risk over similar time horizon. If you would invest 954.00 in Shanghai Material Trading on September 5, 2024 and sell it today you would earn a total of 183.00 from holding Shanghai Material Trading or generate 19.18% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Hangzhou Gaoxin Rubber vs. Shanghai Material Trading
Performance |
| Timeline |
| Hangzhou Gaoxin Rubber |
| Shanghai Material Trading |
Hangzhou Gaoxin and Shanghai Material Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Hangzhou Gaoxin and Shanghai Material
The main advantage of trading using opposite Hangzhou Gaoxin and Shanghai Material positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hangzhou Gaoxin position performs unexpectedly, Shanghai Material 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 Shanghai Material will offset losses from the drop in Shanghai Material's long position.| Hangzhou Gaoxin vs. Hubei Xingfa Chemicals | Hangzhou Gaoxin vs. Miracll Chemicals Co | Hangzhou Gaoxin vs. Sichuan Hebang Biotechnology | Hangzhou Gaoxin vs. Guangdong Jinming Machinery |
| Shanghai Material vs. Cangzhou Mingzhu Plastic | Shanghai Material vs. Sobute New Materials | Shanghai Material vs. Hangzhou Gaoxin Rubber | Shanghai Material vs. Guangzhou Tinci Materials |
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 Idea Optimizer module to use advanced portfolio builder with pre-computed micro ideas to build optimal portfolio .
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