Correlation Between Meiwu Technology and AKA Brands
Can any of the company-specific risk be diversified away by investing in both Meiwu Technology and AKA Brands 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 AKA Brands 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 AKA Brands Holding, you can compare the effects of market volatilities on Meiwu Technology and AKA Brands 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 AKA Brands. Check out your portfolio center. Please also check ongoing floating volatility patterns of Meiwu Technology and AKA Brands.
Diversification Opportunities for Meiwu Technology and AKA Brands
-0.29 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Meiwu and AKA is -0.29. Overlapping area represents the amount of risk that can be diversified away by holding Meiwu Technology Co and AKA Brands Holding in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on AKA Brands Holding 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 AKA Brands. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of AKA Brands Holding has no effect on the direction of Meiwu Technology i.e., Meiwu Technology and AKA Brands go up and down completely randomly.
Pair Corralation between Meiwu Technology and AKA Brands
Considering the 90-day investment horizon Meiwu Technology is expected to generate 7.73 times less return on investment than AKA Brands. In addition to that, Meiwu Technology is 1.31 times more volatile than AKA Brands Holding. It trades about 0.01 of its total potential returns per unit of risk. AKA Brands Holding is currently generating about 0.09 per unit of volatility. If you would invest 526.00 in AKA Brands Holding on September 12, 2024 and sell it today you would earn a total of 1,510 from holding AKA Brands Holding or generate 287.07% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Meiwu Technology Co vs. AKA Brands Holding
Performance |
| Timeline |
| Meiwu Technology |
| AKA Brands Holding |
Meiwu Technology and AKA Brands Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Meiwu Technology and AKA Brands
The main advantage of trading using opposite Meiwu Technology and AKA Brands positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Meiwu Technology position performs unexpectedly, AKA Brands 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 AKA Brands will offset losses from the drop in AKA Brands' long position.| Meiwu Technology vs. MOGU Inc | Meiwu Technology vs. iPower Inc | Meiwu Technology vs. Jeffs Brands | Meiwu Technology vs. Kidpik Corp |
| AKA Brands vs. Hour Loop | AKA Brands vs. Kidpik Corp | AKA Brands vs. MOGU Inc | AKA Brands vs. Jowell Global |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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