Correlation Between Meiwu Technology and Fast Retailing
Can any of the company-specific risk be diversified away by investing in both Meiwu Technology and Fast Retailing 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 Meiwu Technology and Fast Retailing into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Meiwu Technology Co and Fast Retailing Co, you can compare the effects of market volatilities on Meiwu Technology and Fast Retailing 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 Meiwu Technology with a short position of Fast Retailing. Check out your portfolio center. Please also check ongoing floating volatility patterns of Meiwu Technology and Fast Retailing.
Diversification Opportunities for Meiwu Technology and Fast Retailing
-0.08 | Correlation Coefficient |
Good diversification
The 3 months correlation between Meiwu and Fast is -0.08. Overlapping area represents the amount of risk that can be diversified away by holding Meiwu Technology Co and Fast Retailing Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Fast Retailing and Meiwu Technology 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 Meiwu Technology Co are associated (or correlated) with Fast Retailing. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Fast Retailing has no effect on the direction of Meiwu Technology i.e., Meiwu Technology and Fast Retailing go up and down completely randomly.
Pair Corralation between Meiwu Technology and Fast Retailing
Considering the 90-day investment horizon Meiwu Technology Co is expected to under-perform the Fast Retailing. But the stock apears to be less risky and, when comparing its historical volatility, Meiwu Technology Co is 1.35 times less risky than Fast Retailing. The stock trades about 0.0 of its potential returns per unit of risk. The Fast Retailing Co is currently generating about 0.05 of returns per unit of risk over similar time horizon. If you would invest 20,581 in Fast Retailing Co on September 12, 2024 and sell it today you would earn a total of 13,009 from holding Fast Retailing Co or generate 63.21% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 75.76% |
Values | Daily Returns |
Meiwu Technology Co vs. Fast Retailing Co
Performance |
Timeline |
Meiwu Technology |
Fast Retailing |
Meiwu Technology and Fast Retailing Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Meiwu Technology and Fast Retailing
The main advantage of trading using opposite Meiwu Technology and Fast Retailing positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Meiwu Technology position performs unexpectedly, Fast Retailing 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 Fast Retailing will offset losses from the drop in Fast Retailing's long position.Meiwu Technology vs. MOGU Inc | Meiwu Technology vs. iPower Inc | Meiwu Technology vs. Jeffs Brands | Meiwu Technology vs. Kidpik Corp |
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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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