Correlation Between Dongbang Transport and I Components
Can any of the company-specific risk be diversified away by investing in both Dongbang Transport and I Components at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining Dongbang Transport and I Components into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Dongbang Transport Logistics and i Components Co, you can compare the effects of market volatilities on Dongbang Transport and I Components 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 Dongbang Transport with a short position of I Components. Check out your portfolio center. Please also check ongoing floating volatility patterns of Dongbang Transport and I Components.
Diversification Opportunities for Dongbang Transport and I Components
0.05 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Dongbang and 059100 is 0.05. Overlapping area represents the amount of risk that can be diversified away by holding Dongbang Transport Logistics and i Components Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on i Components and Dongbang Transport 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 Dongbang Transport Logistics are associated (or correlated) with I Components. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of i Components has no effect on the direction of Dongbang Transport i.e., Dongbang Transport and I Components go up and down completely randomly.
Pair Corralation between Dongbang Transport and I Components
Assuming the 90 days trading horizon Dongbang Transport Logistics is expected to under-perform the I Components. In addition to that, Dongbang Transport is 1.77 times more volatile than i Components Co. It trades about -0.1 of its total potential returns per unit of risk. i Components Co is currently generating about 0.05 per unit of volatility. If you would invest 468,500 in i Components Co on October 8, 2024 and sell it today you would earn a total of 16,500 from holding i Components Co or generate 3.52% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Dongbang Transport Logistics vs. i Components Co
Performance |
Timeline |
Dongbang Transport |
i Components |
Dongbang Transport and I Components Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Dongbang Transport and I Components
The main advantage of trading using opposite Dongbang Transport and I Components positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dongbang Transport position performs unexpectedly, I Components 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 I Components will offset losses from the drop in I Components' long position.Dongbang Transport vs. AptaBio Therapeutics | Dongbang Transport vs. Daewoo SBI SPAC | Dongbang Transport vs. Dream Security co | Dongbang Transport vs. Microfriend |
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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 Volatility Analysis module to get historical volatility and risk analysis based on latest market data.
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