Correlation Between Ping An and China Everbright
Specify exactly 2 symbols:
By analyzing existing cross correlation between Ping An Insurance and China Everbright Bank, you can compare the effects of market volatilities on Ping An and China Everbright 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 Ping An with a short position of China Everbright. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ping An and China Everbright.
Diversification Opportunities for Ping An and China Everbright
0.83 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Ping and China is 0.83. Overlapping area represents the amount of risk that can be diversified away by holding Ping An Insurance and China Everbright Bank in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on China Everbright Bank and Ping An 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 Ping An Insurance are associated (or correlated) with China Everbright. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of China Everbright Bank has no effect on the direction of Ping An i.e., Ping An and China Everbright go up and down completely randomly.
Pair Corralation between Ping An and China Everbright
Assuming the 90 days trading horizon Ping An Insurance is expected to generate 1.55 times more return on investment than China Everbright. However, Ping An is 1.55 times more volatile than China Everbright Bank. It trades about 0.17 of its potential returns per unit of risk. China Everbright Bank is currently generating about 0.2 per unit of risk. If you would invest 4,260 in Ping An Insurance on September 12, 2024 and sell it today you would earn a total of 1,302 from holding Ping An Insurance or generate 30.56% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 98.28% |
Values | Daily Returns |
Ping An Insurance vs. China Everbright Bank
Performance |
Timeline |
Ping An Insurance |
China Everbright Bank |
Ping An and China Everbright Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Ping An and China Everbright
The main advantage of trading using opposite Ping An and China Everbright positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ping An position performs unexpectedly, China Everbright 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 China Everbright will offset losses from the drop in China Everbright's long position.Ping An vs. China Petroleum Chemical | Ping An vs. PetroChina Co Ltd | Ping An vs. China Mobile Limited | Ping An vs. Industrial and Commercial |
China Everbright vs. Eastroc Beverage Group | China Everbright vs. HaiXin Foods Co | China Everbright vs. Qingdao Foods Co | China Everbright vs. Shanghai Ziyan Foods |
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 FinTech Suite module to use AI to screen and filter profitable investment opportunities.
Other Complementary Tools
Equity Valuation Check real value of public entities based on technical and fundamental data | |
Commodity Directory Find actively traded commodities issued by global exchanges | |
Pair Correlation Compare performance and examine fundamental relationship between any two equity instruments | |
Equity Search Search for actively traded equities including funds and ETFs from over 30 global markets | |
Equity Forecasting Use basic forecasting models to generate price predictions and determine price momentum |