Correlation Between China Securities and Beijing SuperMap
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By analyzing existing cross correlation between China Securities 800 and Beijing SuperMap Software, you can compare the effects of market volatilities on China Securities and Beijing SuperMap 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 China Securities with a short position of Beijing SuperMap. Check out your portfolio center. Please also check ongoing floating volatility patterns of China Securities and Beijing SuperMap.
Diversification Opportunities for China Securities and Beijing SuperMap
0.86 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between China and Beijing is 0.86. Overlapping area represents the amount of risk that can be diversified away by holding China Securities 800 and Beijing SuperMap Software in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Beijing SuperMap Software and China Securities 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 China Securities 800 are associated (or correlated) with Beijing SuperMap. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Beijing SuperMap Software has no effect on the direction of China Securities i.e., China Securities and Beijing SuperMap go up and down completely randomly.
Pair Corralation between China Securities and Beijing SuperMap
Assuming the 90 days trading horizon China Securities 800 is expected to under-perform the Beijing SuperMap. But the index apears to be less risky and, when comparing its historical volatility, China Securities 800 is 2.69 times less risky than Beijing SuperMap. The index trades about 0.0 of its potential returns per unit of risk. The Beijing SuperMap Software is currently generating about 0.0 of returns per unit of risk over similar time horizon. If you would invest 2,366 in Beijing SuperMap Software on November 28, 2024 and sell it today you would lose (500.00) from holding Beijing SuperMap Software or give up 21.13% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
China Securities 800 vs. Beijing SuperMap Software
Performance |
| Timeline |
China Securities and Beijing SuperMap Volatility Contrast
Predicted Return Density |
| Returns |
China Securities 800
Pair trading matchups for China Securities
Beijing SuperMap Software
Pair trading matchups for Beijing SuperMap
Pair Trading with China Securities and Beijing SuperMap
The main advantage of trading using opposite China Securities and Beijing SuperMap positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if China Securities position performs unexpectedly, Beijing SuperMap 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 Beijing SuperMap will offset losses from the drop in Beijing SuperMap's long position.| China Securities vs. Hainan Haiqi Transportation | China Securities vs. Allwin Telecommunication Co | China Securities vs. Suzhou Mingzhi Technology | China Securities vs. BTG Hotels Group |
| Beijing SuperMap vs. Qumei Furniture Group | Beijing SuperMap vs. Tibet Huayu Mining | Beijing SuperMap vs. Juneyao Airlines | Beijing SuperMap vs. Zijin Mining Group |
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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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