Correlation Between Dongxing Sec and Jinxiandai Information
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By analyzing existing cross correlation between Dongxing Sec Co and Jinxiandai Information Industry, you can compare the effects of market volatilities on Dongxing Sec and Jinxiandai Information 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 Dongxing Sec with a short position of Jinxiandai Information. Check out your portfolio center. Please also check ongoing floating volatility patterns of Dongxing Sec and Jinxiandai Information.
Diversification Opportunities for Dongxing Sec and Jinxiandai Information
0.27 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Dongxing and Jinxiandai is 0.27. Overlapping area represents the amount of risk that can be diversified away by holding Dongxing Sec Co and Jinxiandai Information Industr in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Jinxiandai Information and Dongxing Sec 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 Dongxing Sec Co are associated (or correlated) with Jinxiandai Information. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Jinxiandai Information has no effect on the direction of Dongxing Sec i.e., Dongxing Sec and Jinxiandai Information go up and down completely randomly.
Pair Corralation between Dongxing Sec and Jinxiandai Information
Assuming the 90 days trading horizon Dongxing Sec Co is expected to under-perform the Jinxiandai Information. But the stock apears to be less risky and, when comparing its historical volatility, Dongxing Sec Co is 1.62 times less risky than Jinxiandai Information. The stock trades about -0.09 of its potential returns per unit of risk. The Jinxiandai Information Industry is currently generating about 0.1 of returns per unit of risk over similar time horizon. If you would invest 848.00 in Jinxiandai Information Industry on October 28, 2024 and sell it today you would earn a total of 70.00 from holding Jinxiandai Information Industry or generate 8.25% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Dongxing Sec Co vs. Jinxiandai Information Industr
Performance |
| Timeline |
| Dongxing Sec |
| Jinxiandai Information |
Dongxing Sec and Jinxiandai Information Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Dongxing Sec and Jinxiandai Information
The main advantage of trading using opposite Dongxing Sec and Jinxiandai Information positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dongxing Sec position performs unexpectedly, Jinxiandai Information 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 Jinxiandai Information will offset losses from the drop in Jinxiandai Information's long position.| Dongxing Sec vs. Ping An Insurance | Dongxing Sec vs. Offshore Oil Engineering | Dongxing Sec vs. Citic Offshore Helicopter | Dongxing Sec vs. Shandong Polymer Biochemicals |
| Jinxiandai Information vs. Bank of China | Jinxiandai Information vs. Kweichow Moutai Co | Jinxiandai Information vs. PetroChina Co Ltd | Jinxiandai Information vs. Bank of Communications |
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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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