Correlation Between Fangdd Network and New York
Can any of the company-specific risk be diversified away by investing in both Fangdd Network and New York 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 Fangdd Network and New York into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Fangdd Network Group and New York City, you can compare the effects of market volatilities on Fangdd Network and New York 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 Fangdd Network with a short position of New York. Check out your portfolio center. Please also check ongoing floating volatility patterns of Fangdd Network and New York.
Diversification Opportunities for Fangdd Network and New York
-0.34 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Fangdd and New is -0.34. Overlapping area represents the amount of risk that can be diversified away by holding Fangdd Network Group and New York City in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on New York City and Fangdd Network 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 Fangdd Network Group are associated (or correlated) with New York. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of New York City has no effect on the direction of Fangdd Network i.e., Fangdd Network and New York go up and down completely randomly.
Pair Corralation between Fangdd Network and New York
Considering the 90-day investment horizon Fangdd Network Group is expected to generate 4.83 times more return on investment than New York. However, Fangdd Network is 4.83 times more volatile than New York City. It trades about 0.01 of its potential returns per unit of risk. New York City is currently generating about 0.02 per unit of risk. If you would invest 1,485 in Fangdd Network Group on January 7, 2025 and sell it today you would lose (1,460) from holding Fangdd Network Group or give up 98.32% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Fangdd Network Group vs. New York City
Performance |
| Timeline |
| Fangdd Network Group |
| New York City |
Fangdd Network and New York Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Fangdd Network and New York
The main advantage of trading using opposite Fangdd Network and New York positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Fangdd Network position performs unexpectedly, New York 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 New York will offset losses from the drop in New York's long position.| Fangdd Network vs. Southcorp Capital | Fangdd Network vs. Frp Holdings Ord | Fangdd Network vs. Ucommune International | Fangdd Network vs. Ohmyhome Limited Ordinary |
| New York vs. Frp Holdings Ord | New York vs. Marcus Millichap | New York vs. J W Mays | New York vs. Anywhere Real Estate |
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 Theme Ratings module to determine theme ratings based on digital equity recommendations. Macroaxis theme ratings are based on combination of fundamental analysis and risk-adjusted market performance.
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