Correlation Between Guangzhou Seagull and Shanghai Metersbonwe
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By analyzing existing cross correlation between Guangzhou Seagull Kitchen and Shanghai Metersbonwe FashionAccessories, you can compare the effects of market volatilities on Guangzhou Seagull and Shanghai Metersbonwe 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 Seagull with a short position of Shanghai Metersbonwe. Check out your portfolio center. Please also check ongoing floating volatility patterns of Guangzhou Seagull and Shanghai Metersbonwe.
Diversification Opportunities for Guangzhou Seagull and Shanghai Metersbonwe
0.88 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Guangzhou and Shanghai is 0.88. Overlapping area represents the amount of risk that can be diversified away by holding Guangzhou Seagull Kitchen and Shanghai Metersbonwe FashionAc in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Shanghai Metersbonwe and Guangzhou Seagull 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 Seagull Kitchen are associated (or correlated) with Shanghai Metersbonwe. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Shanghai Metersbonwe has no effect on the direction of Guangzhou Seagull i.e., Guangzhou Seagull and Shanghai Metersbonwe go up and down completely randomly.
Pair Corralation between Guangzhou Seagull and Shanghai Metersbonwe
Assuming the 90 days trading horizon Guangzhou Seagull Kitchen is expected to under-perform the Shanghai Metersbonwe. But the stock apears to be less risky and, when comparing its historical volatility, Guangzhou Seagull Kitchen is 1.11 times less risky than Shanghai Metersbonwe. The stock trades about -0.02 of its potential returns per unit of risk. The Shanghai Metersbonwe FashionAccessories is currently generating about 0.01 of returns per unit of risk over similar time horizon. If you would invest 224.00 in Shanghai Metersbonwe FashionAccessories on September 3, 2024 and sell it today you would lose (22.00) from holding Shanghai Metersbonwe FashionAccessories or give up 9.82% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Guangzhou Seagull Kitchen vs. Shanghai Metersbonwe FashionAc
Performance |
| Timeline |
| Guangzhou Seagull Kitchen |
| Shanghai Metersbonwe |
Guangzhou Seagull and Shanghai Metersbonwe Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Guangzhou Seagull and Shanghai Metersbonwe
The main advantage of trading using opposite Guangzhou Seagull and Shanghai Metersbonwe positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Guangzhou Seagull position performs unexpectedly, Shanghai Metersbonwe 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 Metersbonwe will offset losses from the drop in Shanghai Metersbonwe's long position.| Guangzhou Seagull vs. Sunwave Communications Co | Guangzhou Seagull vs. Tongyu Communication | Guangzhou Seagull vs. Iat Automobile Technology | Guangzhou Seagull vs. Andon Health Co |
| Shanghai Metersbonwe vs. PetroChina Co Ltd | Shanghai Metersbonwe vs. China Mobile Limited | Shanghai Metersbonwe vs. Industrial and Commercial | Shanghai Metersbonwe vs. China Life Insurance |
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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