Correlation Between Camelot Electronics and Digital China
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By analyzing existing cross correlation between Camelot Electronics Technology and Digital China Information, you can compare the effects of market volatilities on Camelot Electronics and Digital China 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 Camelot Electronics with a short position of Digital China. Check out your portfolio center. Please also check ongoing floating volatility patterns of Camelot Electronics and Digital China.
Diversification Opportunities for Camelot Electronics and Digital China
0.82 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Camelot and Digital is 0.82. Overlapping area represents the amount of risk that can be diversified away by holding Camelot Electronics Technology and Digital China Information in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Digital China Information and Camelot Electronics 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 Camelot Electronics Technology are associated (or correlated) with Digital China. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Digital China Information has no effect on the direction of Camelot Electronics i.e., Camelot Electronics and Digital China go up and down completely randomly.
Pair Corralation between Camelot Electronics and Digital China
Assuming the 90 days trading horizon Camelot Electronics is expected to generate 2.33 times less return on investment than Digital China. But when comparing it to its historical volatility, Camelot Electronics Technology is 1.69 times less risky than Digital China. It trades about 0.08 of its potential returns per unit of risk. Digital China Information is currently generating about 0.11 of returns per unit of risk over similar time horizon. If you would invest 1,181 in Digital China Information on December 25, 2024 and sell it today you would earn a total of 255.00 from holding Digital China Information or generate 21.59% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Camelot Electronics Technology vs. Digital China Information
Performance |
Timeline |
Camelot Electronics |
Digital China Information |
Camelot Electronics and Digital China Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Camelot Electronics and Digital China
The main advantage of trading using opposite Camelot Electronics and Digital China positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Camelot Electronics position performs unexpectedly, Digital China 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 Digital China will offset losses from the drop in Digital China's long position.The idea behind Camelot Electronics Technology and Digital China Information pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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