Correlation Between Xinhua Winshare and Shenyang Huitian
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By analyzing existing cross correlation between Xinhua Winshare Publishing and Shenyang Huitian Thermal, you can compare the effects of market volatilities on Xinhua Winshare and Shenyang Huitian 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 Xinhua Winshare with a short position of Shenyang Huitian. Check out your portfolio center. Please also check ongoing floating volatility patterns of Xinhua Winshare and Shenyang Huitian.
Diversification Opportunities for Xinhua Winshare and Shenyang Huitian
0.07 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Xinhua and Shenyang is 0.07. Overlapping area represents the amount of risk that can be diversified away by holding Xinhua Winshare Publishing and Shenyang Huitian Thermal in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Shenyang Huitian Thermal and Xinhua Winshare 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 Xinhua Winshare Publishing are associated (or correlated) with Shenyang Huitian. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Shenyang Huitian Thermal has no effect on the direction of Xinhua Winshare i.e., Xinhua Winshare and Shenyang Huitian go up and down completely randomly.
Pair Corralation between Xinhua Winshare and Shenyang Huitian
Assuming the 90 days trading horizon Xinhua Winshare Publishing is expected to under-perform the Shenyang Huitian. But the stock apears to be less risky and, when comparing its historical volatility, Xinhua Winshare Publishing is 1.45 times less risky than Shenyang Huitian. The stock trades about -0.23 of its potential returns per unit of risk. The Shenyang Huitian Thermal is currently generating about -0.14 of returns per unit of risk over similar time horizon. If you would invest 356.00 in Shenyang Huitian Thermal on October 28, 2024 and sell it today you would lose (22.00) from holding Shenyang Huitian Thermal or give up 6.18% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Xinhua Winshare Publishing vs. Shenyang Huitian Thermal
Performance |
| Timeline |
| Xinhua Winshare Publ |
| Shenyang Huitian Thermal |
Xinhua Winshare and Shenyang Huitian Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Xinhua Winshare and Shenyang Huitian
The main advantage of trading using opposite Xinhua Winshare and Shenyang Huitian positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Xinhua Winshare position performs unexpectedly, Shenyang Huitian 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 Shenyang Huitian will offset losses from the drop in Shenyang Huitian's long position.| Xinhua Winshare vs. Anhui Fuhuang Steel | Xinhua Winshare vs. Shenzhen MYS Environmental | Xinhua Winshare vs. Tongxing Environmental Protection | Xinhua Winshare vs. Tsingtao Brewery Co |
| Shenyang Huitian vs. Meinian Onehealth Healthcare | Shenyang Huitian vs. Everjoy Health Group | Shenyang Huitian vs. Dezhan HealthCare Co | Shenyang Huitian vs. Shantui Construction Machinery |
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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