Correlation Between Shanghai Metersbonwe and Shenzhen Hifuture
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By analyzing existing cross correlation between Shanghai Metersbonwe FashionAccessories and Shenzhen Hifuture Electric, you can compare the effects of market volatilities on Shanghai Metersbonwe and Shenzhen Hifuture 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 Shanghai Metersbonwe with a short position of Shenzhen Hifuture. Check out your portfolio center. Please also check ongoing floating volatility patterns of Shanghai Metersbonwe and Shenzhen Hifuture.
Diversification Opportunities for Shanghai Metersbonwe and Shenzhen Hifuture
0.0 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Shanghai and Shenzhen is 0.0. Overlapping area represents the amount of risk that can be diversified away by holding Shanghai Metersbonwe FashionAc and Shenzhen Hifuture Electric in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Shenzhen Hifuture and Shanghai Metersbonwe 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 Shanghai Metersbonwe FashionAccessories are associated (or correlated) with Shenzhen Hifuture. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Shenzhen Hifuture has no effect on the direction of Shanghai Metersbonwe i.e., Shanghai Metersbonwe and Shenzhen Hifuture go up and down completely randomly.
Pair Corralation between Shanghai Metersbonwe and Shenzhen Hifuture
Assuming the 90 days trading horizon Shanghai Metersbonwe is expected to generate 1.72 times less return on investment than Shenzhen Hifuture. In addition to that, Shanghai Metersbonwe is 1.29 times more volatile than Shenzhen Hifuture Electric. It trades about 0.11 of its total potential returns per unit of risk. Shenzhen Hifuture Electric is currently generating about 0.24 per unit of volatility. If you would invest 241.00 in Shenzhen Hifuture Electric on August 31, 2024 and sell it today you would earn a total of 40.00 from holding Shenzhen Hifuture Electric or generate 16.6% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Flat |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Shanghai Metersbonwe FashionAc vs. Shenzhen Hifuture Electric
Performance |
| Timeline |
| Shanghai Metersbonwe |
| Shenzhen Hifuture |
Shanghai Metersbonwe and Shenzhen Hifuture Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Shanghai Metersbonwe and Shenzhen Hifuture
The main advantage of trading using opposite Shanghai Metersbonwe and Shenzhen Hifuture positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Shanghai Metersbonwe position performs unexpectedly, Shenzhen Hifuture 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 Shenzhen Hifuture will offset losses from the drop in Shenzhen Hifuture's long position.| Shanghai Metersbonwe vs. China State Construction | Shanghai Metersbonwe vs. China Merchants Shekou | Shanghai Metersbonwe vs. Huafa Industrial Co | Shanghai Metersbonwe vs. China International Capital |
| Shenzhen Hifuture vs. Anhui Gujing Distillery | Shenzhen Hifuture vs. Tonghua Grape Wine | Shenzhen Hifuture vs. Shanghai CEO Environmental | Shenzhen Hifuture vs. Henan Shuanghui Investment |
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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