Correlation Between Songz Automobile and Jinsanjiang Silicon
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By analyzing existing cross correlation between Songz Automobile Air and Jinsanjiang Silicon Material, you can compare the effects of market volatilities on Songz Automobile and Jinsanjiang Silicon 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 Songz Automobile with a short position of Jinsanjiang Silicon. Check out your portfolio center. Please also check ongoing floating volatility patterns of Songz Automobile and Jinsanjiang Silicon.
Diversification Opportunities for Songz Automobile and Jinsanjiang Silicon
0.54 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Songz and Jinsanjiang is 0.54. Overlapping area represents the amount of risk that can be diversified away by holding Songz Automobile Air and Jinsanjiang Silicon Material in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Jinsanjiang Silicon and Songz Automobile 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 Songz Automobile Air are associated (or correlated) with Jinsanjiang Silicon. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Jinsanjiang Silicon has no effect on the direction of Songz Automobile i.e., Songz Automobile and Jinsanjiang Silicon go up and down completely randomly.
Pair Corralation between Songz Automobile and Jinsanjiang Silicon
Assuming the 90 days trading horizon Songz Automobile Air is expected to under-perform the Jinsanjiang Silicon. But the stock apears to be less risky and, when comparing its historical volatility, Songz Automobile Air is 1.52 times less risky than Jinsanjiang Silicon. The stock trades about 0.0 of its potential returns per unit of risk. The Jinsanjiang Silicon Material is currently generating about 0.01 of returns per unit of risk over similar time horizon. If you would invest 1,278 in Jinsanjiang Silicon Material on October 18, 2024 and sell it today you would lose (230.00) from holding Jinsanjiang Silicon Material or give up 18.0% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Songz Automobile Air vs. Jinsanjiang Silicon Material
Performance |
| Timeline |
| Songz Automobile Air |
| Jinsanjiang Silicon |
Songz Automobile and Jinsanjiang Silicon Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Songz Automobile and Jinsanjiang Silicon
The main advantage of trading using opposite Songz Automobile and Jinsanjiang Silicon positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Songz Automobile position performs unexpectedly, Jinsanjiang Silicon 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 Jinsanjiang Silicon will offset losses from the drop in Jinsanjiang Silicon's long position.| Songz Automobile vs. Shenzhen Bioeasy Biotechnology | Songz Automobile vs. Bloomage Biotechnology Corp | Songz Automobile vs. Olympic Circuit Technology | Songz Automobile vs. Sichuan Hebang Biotechnology |
| Jinsanjiang Silicon vs. Soochow Suzhou Industrial | Jinsanjiang Silicon vs. Gem Year Industrial Co | Jinsanjiang Silicon vs. Marssenger Kitchenware Co | Jinsanjiang Silicon vs. Bosera CMSK Industrial |
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 Volatility Analysis module to get historical volatility and risk analysis based on latest market data.
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