Correlation Between Shandong Polymer and Heilongjiang Transport
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By analyzing existing cross correlation between Shandong Polymer Biochemicals and Heilongjiang Transport Development, you can compare the effects of market volatilities on Shandong Polymer and Heilongjiang Transport 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 Shandong Polymer with a short position of Heilongjiang Transport. Check out your portfolio center. Please also check ongoing floating volatility patterns of Shandong Polymer and Heilongjiang Transport.
Diversification Opportunities for Shandong Polymer and Heilongjiang Transport
0.78 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Shandong and Heilongjiang is 0.78. Overlapping area represents the amount of risk that can be diversified away by holding Shandong Polymer Biochemicals and Heilongjiang Transport Develop in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Heilongjiang Transport and Shandong Polymer 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 Shandong Polymer Biochemicals are associated (or correlated) with Heilongjiang Transport. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Heilongjiang Transport has no effect on the direction of Shandong Polymer i.e., Shandong Polymer and Heilongjiang Transport go up and down completely randomly.
Pair Corralation between Shandong Polymer and Heilongjiang Transport
Assuming the 90 days trading horizon Shandong Polymer Biochemicals is expected to generate 1.29 times more return on investment than Heilongjiang Transport. However, Shandong Polymer is 1.29 times more volatile than Heilongjiang Transport Development. It trades about 0.13 of its potential returns per unit of risk. Heilongjiang Transport Development is currently generating about -0.15 per unit of risk. If you would invest 412.00 in Shandong Polymer Biochemicals on October 26, 2024 and sell it today you would earn a total of 24.00 from holding Shandong Polymer Biochemicals or generate 5.83% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Shandong Polymer Biochemicals vs. Heilongjiang Transport Develop
Performance |
| Timeline |
| Shandong Polymer Bio |
| Heilongjiang Transport |
Shandong Polymer and Heilongjiang Transport Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Shandong Polymer and Heilongjiang Transport
The main advantage of trading using opposite Shandong Polymer and Heilongjiang Transport positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Shandong Polymer position performs unexpectedly, Heilongjiang Transport 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 Heilongjiang Transport will offset losses from the drop in Heilongjiang Transport's long position.| Shandong Polymer vs. Zijin Mining Group | Shandong Polymer vs. Wanhua Chemical Group | Shandong Polymer vs. Baoshan Iron Steel | Shandong Polymer vs. Shandong Gold Mining |
| Heilongjiang Transport vs. PetroChina Co Ltd | Heilongjiang Transport vs. China Mobile Limited | Heilongjiang Transport vs. CNOOC Limited | Heilongjiang Transport vs. Ping An Insurance |
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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