Correlation Between U Power and Centessa Pharmaceuticals
Can any of the company-specific risk be diversified away by investing in both U Power and Centessa Pharmaceuticals 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 U Power and Centessa Pharmaceuticals into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between U Power Limited and Centessa Pharmaceuticals PLC, you can compare the effects of market volatilities on U Power and Centessa Pharmaceuticals 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 U Power with a short position of Centessa Pharmaceuticals. Check out your portfolio center. Please also check ongoing floating volatility patterns of U Power and Centessa Pharmaceuticals.
Diversification Opportunities for U Power and Centessa Pharmaceuticals
-0.36 | Correlation Coefficient |
Very good diversification
The 3 months correlation between UCAR and Centessa is -0.36. Overlapping area represents the amount of risk that can be diversified away by holding U Power Limited and Centessa Pharmaceuticals PLC in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Centessa Pharmaceuticals and U Power 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 U Power Limited are associated (or correlated) with Centessa Pharmaceuticals. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Centessa Pharmaceuticals has no effect on the direction of U Power i.e., U Power and Centessa Pharmaceuticals go up and down completely randomly.
Pair Corralation between U Power and Centessa Pharmaceuticals
Given the investment horizon of 90 days U Power Limited is expected to generate 15.44 times more return on investment than Centessa Pharmaceuticals. However, U Power is 15.44 times more volatile than Centessa Pharmaceuticals PLC. It trades about 0.05 of its potential returns per unit of risk. Centessa Pharmaceuticals PLC is currently generating about 0.1 per unit of risk. If you would invest 0.00 in U Power Limited on September 20, 2024 and sell it today you would earn a total of 665.00 from holding U Power Limited or generate 9.223372036854776E16% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 85.05% |
| Values | Daily Returns |
U Power Limited vs. Centessa Pharmaceuticals PLC
Performance |
| Timeline |
| U Power Limited |
| Centessa Pharmaceuticals |
U Power and Centessa Pharmaceuticals Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with U Power and Centessa Pharmaceuticals
The main advantage of trading using opposite U Power and Centessa Pharmaceuticals positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if U Power position performs unexpectedly, Centessa Pharmaceuticals 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 Centessa Pharmaceuticals will offset losses from the drop in Centessa Pharmaceuticals' long position.| U Power vs. Kaixin Auto Holdings | U Power vs. Uxin | U Power vs. SunCar Technology Group | U Power vs. Carvana Co |
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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