Correlation Between Industrial Bank and Beijing Mainstreets
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By analyzing existing cross correlation between Industrial Bank Co and Beijing Mainstreets Investment, you can compare the effects of market volatilities on Industrial Bank and Beijing Mainstreets 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 Industrial Bank with a short position of Beijing Mainstreets. Check out your portfolio center. Please also check ongoing floating volatility patterns of Industrial Bank and Beijing Mainstreets.
Diversification Opportunities for Industrial Bank and Beijing Mainstreets
-0.74 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Industrial and Beijing is -0.74. Overlapping area represents the amount of risk that can be diversified away by holding Industrial Bank Co and Beijing Mainstreets Investment in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Beijing Mainstreets and Industrial Bank 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 Industrial Bank Co are associated (or correlated) with Beijing Mainstreets. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Beijing Mainstreets has no effect on the direction of Industrial Bank i.e., Industrial Bank and Beijing Mainstreets go up and down completely randomly.
Pair Corralation between Industrial Bank and Beijing Mainstreets
Assuming the 90 days trading horizon Industrial Bank is expected to generate 17.96 times less return on investment than Beijing Mainstreets. But when comparing it to its historical volatility, Industrial Bank Co is 2.73 times less risky than Beijing Mainstreets. It trades about 0.02 of its potential returns per unit of risk. Beijing Mainstreets Investment is currently generating about 0.14 of returns per unit of risk over similar time horizon. If you would invest 185.00 in Beijing Mainstreets Investment on October 10, 2024 and sell it today you would earn a total of 60.00 from holding Beijing Mainstreets Investment or generate 32.43% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Industrial Bank Co vs. Beijing Mainstreets Investment
Performance |
Timeline |
Industrial Bank |
Beijing Mainstreets |
Industrial Bank and Beijing Mainstreets Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Industrial Bank and Beijing Mainstreets
The main advantage of trading using opposite Industrial Bank and Beijing Mainstreets positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Industrial Bank position performs unexpectedly, Beijing Mainstreets 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 Mainstreets will offset losses from the drop in Beijing Mainstreets' long position.Industrial Bank vs. Shenzhen Noposion Agrochemicals | Industrial Bank vs. Shandong Polymer Biochemicals | Industrial Bank vs. Pengxin International Mining | Industrial Bank vs. China Mobile Limited |
Beijing Mainstreets vs. Quectel Wireless Solutions | Beijing Mainstreets vs. Xiangyang Automobile Bearing | Beijing Mainstreets vs. SUNSEA Telecommunications Co | Beijing Mainstreets vs. China Mobile Limited |
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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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