Correlation Between Playmates Toys and China Datang
Can any of the company-specific risk be diversified away by investing in both Playmates Toys and China Datang 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 Playmates Toys and China Datang into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Playmates Toys Limited and China Datang, you can compare the effects of market volatilities on Playmates Toys and China Datang 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 Playmates Toys with a short position of China Datang. Check out your portfolio center. Please also check ongoing floating volatility patterns of Playmates Toys and China Datang.
Diversification Opportunities for Playmates Toys and China Datang
-0.25 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Playmates and China is -0.25. Overlapping area represents the amount of risk that can be diversified away by holding Playmates Toys Limited and China Datang in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on China Datang and Playmates Toys 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 Playmates Toys Limited are associated (or correlated) with China Datang. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of China Datang has no effect on the direction of Playmates Toys i.e., Playmates Toys and China Datang go up and down completely randomly.
Pair Corralation between Playmates Toys and China Datang
Assuming the 90 days horizon Playmates Toys Limited is expected to generate 4.64 times more return on investment than China Datang. However, Playmates Toys is 4.64 times more volatile than China Datang. It trades about 0.03 of its potential returns per unit of risk. China Datang is currently generating about 0.01 per unit of risk. If you would invest 6.80 in Playmates Toys Limited on October 25, 2024 and sell it today you would lose (0.30) from holding Playmates Toys Limited or give up 4.41% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Playmates Toys Limited vs. China Datang
Performance |
| Timeline |
| Playmates Toys |
| China Datang |
Playmates Toys and China Datang Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Playmates Toys and China Datang
The main advantage of trading using opposite Playmates Toys and China Datang positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Playmates Toys position performs unexpectedly, China Datang 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 China Datang will offset losses from the drop in China Datang's long position.| Playmates Toys vs. China Datang | Playmates Toys vs. AIR PRODCHEMICALS | Playmates Toys vs. Haverty Furniture Companies | Playmates Toys vs. Addus HomeCare |
| China Datang vs. Charter Communications | China Datang vs. OPERA SOFTWARE | China Datang vs. FORMPIPE SOFTWARE AB | China Datang vs. USU Software AG |
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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