Correlation Between Baoshan Iron and Sinosteel Luonai
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By analyzing existing cross correlation between Baoshan Iron Steel and Sinosteel Luonai Materials, you can compare the effects of market volatilities on Baoshan Iron and Sinosteel Luonai 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 Baoshan Iron with a short position of Sinosteel Luonai. Check out your portfolio center. Please also check ongoing floating volatility patterns of Baoshan Iron and Sinosteel Luonai.
Diversification Opportunities for Baoshan Iron and Sinosteel Luonai
0.2 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Baoshan and Sinosteel is 0.2. Overlapping area represents the amount of risk that can be diversified away by holding Baoshan Iron Steel and Sinosteel Luonai Materials in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Sinosteel Luonai Mat and Baoshan Iron 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 Baoshan Iron Steel are associated (or correlated) with Sinosteel Luonai. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Sinosteel Luonai Mat has no effect on the direction of Baoshan Iron i.e., Baoshan Iron and Sinosteel Luonai go up and down completely randomly.
Pair Corralation between Baoshan Iron and Sinosteel Luonai
Assuming the 90 days trading horizon Baoshan Iron is expected to generate 1.18 times less return on investment than Sinosteel Luonai. In addition to that, Baoshan Iron is 1.52 times more volatile than Sinosteel Luonai Materials. It trades about 0.05 of its total potential returns per unit of risk. Sinosteel Luonai Materials is currently generating about 0.1 per unit of volatility. If you would invest 366.00 in Sinosteel Luonai Materials on November 7, 2024 and sell it today you would earn a total of 7.00 from holding Sinosteel Luonai Materials or generate 1.91% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Baoshan Iron Steel vs. Sinosteel Luonai Materials
Performance |
| Timeline |
| Baoshan Iron Steel |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Weak
| Sinosteel Luonai Mat |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
Baoshan Iron and Sinosteel Luonai Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Baoshan Iron and Sinosteel Luonai
The main advantage of trading using opposite Baoshan Iron and Sinosteel Luonai positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Baoshan Iron position performs unexpectedly, Sinosteel Luonai 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 Sinosteel Luonai will offset losses from the drop in Sinosteel Luonai's long position.The idea behind Baoshan Iron Steel and Sinosteel Luonai Materials pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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