Correlation Between Trade Van and Shuang Bang
Can any of the company-specific risk be diversified away by investing in both Trade Van and Shuang Bang 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 Trade Van and Shuang Bang into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Trade Van Information Services and Shuang Bang Industrial, you can compare the effects of market volatilities on Trade Van and Shuang Bang 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 Trade Van with a short position of Shuang Bang. Check out your portfolio center. Please also check ongoing floating volatility patterns of Trade Van and Shuang Bang.
Diversification Opportunities for Trade Van and Shuang Bang
-0.7 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Trade and Shuang is -0.7. Overlapping area represents the amount of risk that can be diversified away by holding Trade Van Information Services and Shuang Bang Industrial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Shuang Bang Industrial and Trade Van 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 Trade Van Information Services are associated (or correlated) with Shuang Bang. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Shuang Bang Industrial has no effect on the direction of Trade Van i.e., Trade Van and Shuang Bang go up and down completely randomly.
Pair Corralation between Trade Van and Shuang Bang
Assuming the 90 days trading horizon Trade Van Information Services is expected to generate 0.55 times more return on investment than Shuang Bang. However, Trade Van Information Services is 1.81 times less risky than Shuang Bang. It trades about 0.21 of its potential returns per unit of risk. Shuang Bang Industrial is currently generating about -0.07 per unit of risk. If you would invest 7,700 in Trade Van Information Services on October 9, 2024 and sell it today you would earn a total of 1,140 from holding Trade Van Information Services or generate 14.81% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Trade Van Information Services vs. Shuang Bang Industrial
Performance |
Timeline |
Trade Van Information |
Shuang Bang Industrial |
Trade Van and Shuang Bang Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Trade Van and Shuang Bang
The main advantage of trading using opposite Trade Van and Shuang Bang positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Trade Van position performs unexpectedly, Shuang Bang 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 Shuang Bang will offset losses from the drop in Shuang Bang's long position.Trade Van vs. Holy Stone Enterprise | Trade Van vs. Walsin Technology Corp | Trade Van vs. Yageo Corp | Trade Van vs. HannStar Board Corp |
Shuang Bang vs. Coremax Corp | Shuang Bang vs. Taiwan Hopax Chemsistry | Shuang Bang vs. Delta Electronics | Shuang Bang vs. China Steel Chemical |
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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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