Correlation Between Autohome and Kuaishou Technology
Can any of the company-specific risk be diversified away by investing in both Autohome and Kuaishou Technology 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 Autohome and Kuaishou Technology into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Autohome and Kuaishou Technology, you can compare the effects of market volatilities on Autohome and Kuaishou Technology 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 Autohome with a short position of Kuaishou Technology. Check out your portfolio center. Please also check ongoing floating volatility patterns of Autohome and Kuaishou Technology.
Diversification Opportunities for Autohome and Kuaishou Technology
-0.01 | Correlation Coefficient |
Good diversification
The 3 months correlation between Autohome and Kuaishou is -0.01. Overlapping area represents the amount of risk that can be diversified away by holding Autohome and Kuaishou Technology in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kuaishou Technology and Autohome 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 Autohome are associated (or correlated) with Kuaishou Technology. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kuaishou Technology has no effect on the direction of Autohome i.e., Autohome and Kuaishou Technology go up and down completely randomly.
Pair Corralation between Autohome and Kuaishou Technology
Given the investment horizon of 90 days Autohome is expected to generate 29.49 times more return on investment than Kuaishou Technology. However, Autohome is 29.49 times more volatile than Kuaishou Technology. It trades about 0.25 of its potential returns per unit of risk. Kuaishou Technology is currently generating about 0.22 per unit of risk. If you would invest 2,619 in Autohome on November 4, 2024 and sell it today you would earn a total of 312.00 from holding Autohome or generate 11.91% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 95.24% |
| Values | Daily Returns |
Autohome vs. Kuaishou Technology
Performance |
| Timeline |
| Autohome |
| Kuaishou Technology |
Autohome and Kuaishou Technology Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Autohome and Kuaishou Technology
The main advantage of trading using opposite Autohome and Kuaishou Technology positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Autohome position performs unexpectedly, Kuaishou Technology 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 Kuaishou Technology will offset losses from the drop in Kuaishou Technology's long position.| Autohome vs. Hello Group | Autohome vs. Weibo Corp | Autohome vs. Tencent Music Entertainment | Autohome vs. DouYu International Holdings |
| Kuaishou Technology vs. Tencent Holdings | Kuaishou Technology vs. Trivago NV | Kuaishou Technology vs. YY Inc Class | Kuaishou Technology vs. DouYu International Holdings |
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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