Correlation Between Kingsoft Cloud and Bm Technologies
Can any of the company-specific risk be diversified away by investing in both Kingsoft Cloud and Bm Technologies 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 Kingsoft Cloud and Bm Technologies into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Kingsoft Cloud Holdings and Bm Technologies, you can compare the effects of market volatilities on Kingsoft Cloud and Bm Technologies 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 Kingsoft Cloud with a short position of Bm Technologies. Check out your portfolio center. Please also check ongoing floating volatility patterns of Kingsoft Cloud and Bm Technologies.
Diversification Opportunities for Kingsoft Cloud and Bm Technologies
0.67 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Kingsoft and BMTX is 0.67. Overlapping area represents the amount of risk that can be diversified away by holding Kingsoft Cloud Holdings and Bm Technologies in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bm Technologies and Kingsoft Cloud 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 Kingsoft Cloud Holdings are associated (or correlated) with Bm Technologies. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bm Technologies has no effect on the direction of Kingsoft Cloud i.e., Kingsoft Cloud and Bm Technologies go up and down completely randomly.
Pair Corralation between Kingsoft Cloud and Bm Technologies
Allowing for the 90-day total investment horizon Kingsoft Cloud Holdings is expected to generate 1.59 times more return on investment than Bm Technologies. However, Kingsoft Cloud is 1.59 times more volatile than Bm Technologies. It trades about 0.23 of its potential returns per unit of risk. Bm Technologies is currently generating about 0.15 per unit of risk. If you would invest 223.00 in Kingsoft Cloud Holdings on August 31, 2024 and sell it today you would earn a total of 478.00 from holding Kingsoft Cloud Holdings or generate 214.35% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Kingsoft Cloud Holdings vs. Bm Technologies
Performance |
Timeline |
Kingsoft Cloud Holdings |
Bm Technologies |
Kingsoft Cloud and Bm Technologies Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Kingsoft Cloud and Bm Technologies
The main advantage of trading using opposite Kingsoft Cloud and Bm Technologies positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Kingsoft Cloud position performs unexpectedly, Bm Technologies 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 Bm Technologies will offset losses from the drop in Bm Technologies' long position.Kingsoft Cloud vs. Oneconnect Financial Technology | Kingsoft Cloud vs. Global Business Travel | Kingsoft Cloud vs. Alight Inc | Kingsoft Cloud vs. CS Disco LLC |
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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 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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