Correlation Between Beijing Jiaman and Union Semiconductor
Specify exactly 2 symbols:
By analyzing existing cross correlation between Beijing Jiaman Dress and Union Semiconductor Co, you can compare the effects of market volatilities on Beijing Jiaman and Union Semiconductor 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 Beijing Jiaman with a short position of Union Semiconductor. Check out your portfolio center. Please also check ongoing floating volatility patterns of Beijing Jiaman and Union Semiconductor.
Diversification Opportunities for Beijing Jiaman and Union Semiconductor
0.9 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Beijing and Union is 0.9. Overlapping area represents the amount of risk that can be diversified away by holding Beijing Jiaman Dress and Union Semiconductor Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Union Semiconductor and Beijing Jiaman 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 Beijing Jiaman Dress are associated (or correlated) with Union Semiconductor. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Union Semiconductor has no effect on the direction of Beijing Jiaman i.e., Beijing Jiaman and Union Semiconductor go up and down completely randomly.
Pair Corralation between Beijing Jiaman and Union Semiconductor
Assuming the 90 days trading horizon Beijing Jiaman Dress is expected to generate 1.32 times more return on investment than Union Semiconductor. However, Beijing Jiaman is 1.32 times more volatile than Union Semiconductor Co. It trades about 0.14 of its potential returns per unit of risk. Union Semiconductor Co is currently generating about -0.17 per unit of risk. If you would invest 2,048 in Beijing Jiaman Dress on September 19, 2024 and sell it today you would earn a total of 133.00 from holding Beijing Jiaman Dress or generate 6.49% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Beijing Jiaman Dress vs. Union Semiconductor Co
Performance |
Timeline |
Beijing Jiaman Dress |
Union Semiconductor |
Beijing Jiaman and Union Semiconductor Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Beijing Jiaman and Union Semiconductor
The main advantage of trading using opposite Beijing Jiaman and Union Semiconductor positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Beijing Jiaman position performs unexpectedly, Union Semiconductor 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 Union Semiconductor will offset losses from the drop in Union Semiconductor's long position.Beijing Jiaman vs. Industrial and Commercial | Beijing Jiaman vs. Agricultural Bank of | Beijing Jiaman vs. China Construction Bank | Beijing Jiaman vs. Bank of China |
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 Risk-Return Analysis module to view associations between returns expected from investment and the risk you assume.
Other Complementary Tools
Portfolio Suggestion Get suggestions outside of your existing asset allocation including your own model portfolios | |
Equity Forecasting Use basic forecasting models to generate price predictions and determine price momentum | |
Transaction History View history of all your transactions and understand their impact on performance | |
Pattern Recognition Use different Pattern Recognition models to time the market across multiple global exchanges | |
Watchlist Optimization Optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm |