Correlation Between Lingyuan Iron and Rising Nonferrous
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By analyzing existing cross correlation between Lingyuan Iron Steel and Rising Nonferrous Metals, you can compare the effects of market volatilities on Lingyuan Iron and Rising Nonferrous 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 Lingyuan Iron with a short position of Rising Nonferrous. Check out your portfolio center. Please also check ongoing floating volatility patterns of Lingyuan Iron and Rising Nonferrous.
Diversification Opportunities for Lingyuan Iron and Rising Nonferrous
0.66 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Lingyuan and Rising is 0.66. Overlapping area represents the amount of risk that can be diversified away by holding Lingyuan Iron Steel and Rising Nonferrous Metals in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Rising Nonferrous Metals and Lingyuan 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 Lingyuan Iron Steel are associated (or correlated) with Rising Nonferrous. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Rising Nonferrous Metals has no effect on the direction of Lingyuan Iron i.e., Lingyuan Iron and Rising Nonferrous go up and down completely randomly.
Pair Corralation between Lingyuan Iron and Rising Nonferrous
Assuming the 90 days trading horizon Lingyuan Iron Steel is expected to under-perform the Rising Nonferrous. But the stock apears to be less risky and, when comparing its historical volatility, Lingyuan Iron Steel is 1.35 times less risky than Rising Nonferrous. The stock trades about -0.64 of its potential returns per unit of risk. The Rising Nonferrous Metals is currently generating about 0.03 of returns per unit of risk over similar time horizon. If you would invest 2,952 in Rising Nonferrous Metals on October 14, 2024 and sell it today you would earn a total of 32.00 from holding Rising Nonferrous Metals or generate 1.08% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Lingyuan Iron Steel vs. Rising Nonferrous Metals
Performance |
| Timeline |
| Lingyuan Iron Steel |
| Rising Nonferrous Metals |
Lingyuan Iron and Rising Nonferrous Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Lingyuan Iron and Rising Nonferrous
The main advantage of trading using opposite Lingyuan Iron and Rising Nonferrous positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Lingyuan Iron position performs unexpectedly, Rising Nonferrous 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 Rising Nonferrous will offset losses from the drop in Rising Nonferrous' long position.| Lingyuan Iron vs. Iat Automobile Technology | Lingyuan Iron vs. ROPEOK Technology Group | Lingyuan Iron vs. Guangdong Xiongsu Technology | Lingyuan Iron vs. Hubeiyichang Transportation Group |
| Rising Nonferrous vs. Shenzhen MYS Environmental | Rising Nonferrous vs. Hangzhou Guotai Environmental | Rising Nonferrous vs. Lingyuan Iron Steel | Rising Nonferrous vs. Penyao Environmental Protection |
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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
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