Correlation Between Borqs Technologies and Digital Brands
Can any of the company-specific risk be diversified away by investing in both Borqs Technologies and Digital 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 Borqs Technologies and Digital Brands into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Borqs Technologies and Digital Brands Group, you can compare the effects of market volatilities on Borqs Technologies and Digital 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 Borqs Technologies with a short position of Digital Brands. Check out your portfolio center. Please also check ongoing floating volatility patterns of Borqs Technologies and Digital Brands.
Diversification Opportunities for Borqs Technologies and Digital Brands
0.72 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Borqs and Digital is 0.72. Overlapping area represents the amount of risk that can be diversified away by holding Borqs Technologies and Digital Brands Group in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Digital Brands Group and Borqs Technologies 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 Borqs Technologies are associated (or correlated) with Digital Brands. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Digital Brands Group has no effect on the direction of Borqs Technologies i.e., Borqs Technologies and Digital Brands go up and down completely randomly.
Pair Corralation between Borqs Technologies and Digital Brands
Given the investment horizon of 90 days Borqs Technologies is expected to generate 0.51 times more return on investment than Digital Brands. However, Borqs Technologies is 1.94 times less risky than Digital Brands. It trades about 0.02 of its potential returns per unit of risk. Digital Brands Group is currently generating about -0.09 per unit of risk. If you would invest 22.00 in Borqs Technologies on September 25, 2024 and sell it today you would lose (2.00) from holding Borqs Technologies or give up 9.09% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 27.97% |
Values | Daily Returns |
Borqs Technologies vs. Digital Brands Group
Performance |
Timeline |
Borqs Technologies |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
Digital Brands Group |
Borqs Technologies and Digital Brands Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Borqs Technologies and Digital Brands
The main advantage of trading using opposite Borqs Technologies and Digital Brands positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Borqs Technologies position performs unexpectedly, Digital 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 Digital Brands will offset losses from the drop in Digital Brands' long position.Borqs Technologies vs. CXApp Inc | Borqs Technologies vs. Trust Stamp | Borqs Technologies vs. Freight Technologies | Borqs Technologies vs. Infobird Co |
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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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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