Correlation Between Fangdd Network and Cinemark Holdings
Can any of the company-specific risk be diversified away by investing in both Fangdd Network and Cinemark Holdings 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 Cinemark Holdings 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 Cinemark Holdings, you can compare the effects of market volatilities on Fangdd Network and Cinemark Holdings 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 Cinemark Holdings. Check out your portfolio center. Please also check ongoing floating volatility patterns of Fangdd Network and Cinemark Holdings.
Diversification Opportunities for Fangdd Network and Cinemark Holdings
-0.32 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Fangdd and Cinemark is -0.32. Overlapping area represents the amount of risk that can be diversified away by holding Fangdd Network Group and Cinemark Holdings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Cinemark Holdings 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 Cinemark Holdings. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Cinemark Holdings has no effect on the direction of Fangdd Network i.e., Fangdd Network and Cinemark Holdings go up and down completely randomly.
Pair Corralation between Fangdd Network and Cinemark Holdings
Considering the 90-day investment horizon Fangdd Network Group is expected to generate 7.67 times more return on investment than Cinemark Holdings. However, Fangdd Network is 7.67 times more volatile than Cinemark Holdings. It trades about 0.02 of its potential returns per unit of risk. Cinemark Holdings is currently generating about 0.1 per unit of risk. If you would invest 1,290 in Fangdd Network Group on September 2, 2024 and sell it today you would lose (1,232) from holding Fangdd Network Group or give up 95.5% 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. Cinemark Holdings
Performance |
Timeline |
Fangdd Network Group |
Cinemark Holdings |
Fangdd Network and Cinemark Holdings Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Fangdd Network and Cinemark Holdings
The main advantage of trading using opposite Fangdd Network and Cinemark Holdings positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Fangdd Network position performs unexpectedly, Cinemark Holdings 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 Cinemark Holdings will offset losses from the drop in Cinemark Holdings' long position.Fangdd Network vs. MDJM | Fangdd Network vs. Southcorp Capital | Fangdd Network vs. Frp Holdings Ord | Fangdd Network vs. Ucommune International |
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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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