Correlation Between Jinsanjiang Silicon and Guizhou BroadcastingTV
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By analyzing existing cross correlation between Jinsanjiang Silicon Material and Guizhou BroadcastingTV Info, you can compare the effects of market volatilities on Jinsanjiang Silicon and Guizhou BroadcastingTV 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 Jinsanjiang Silicon with a short position of Guizhou BroadcastingTV. Check out your portfolio center. Please also check ongoing floating volatility patterns of Jinsanjiang Silicon and Guizhou BroadcastingTV.
Diversification Opportunities for Jinsanjiang Silicon and Guizhou BroadcastingTV
0.94 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Jinsanjiang and Guizhou is 0.94. Overlapping area represents the amount of risk that can be diversified away by holding Jinsanjiang Silicon Material and Guizhou BroadcastingTV Info in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Guizhou BroadcastingTV and Jinsanjiang Silicon 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 Jinsanjiang Silicon Material are associated (or correlated) with Guizhou BroadcastingTV. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Guizhou BroadcastingTV has no effect on the direction of Jinsanjiang Silicon i.e., Jinsanjiang Silicon and Guizhou BroadcastingTV go up and down completely randomly.
Pair Corralation between Jinsanjiang Silicon and Guizhou BroadcastingTV
Assuming the 90 days trading horizon Jinsanjiang Silicon Material is expected to generate 1.27 times more return on investment than Guizhou BroadcastingTV. However, Jinsanjiang Silicon is 1.27 times more volatile than Guizhou BroadcastingTV Info. It trades about 0.03 of its potential returns per unit of risk. Guizhou BroadcastingTV Info is currently generating about 0.03 per unit of risk. If you would invest 1,161 in Jinsanjiang Silicon Material on September 20, 2024 and sell it today you would earn a total of 62.00 from holding Jinsanjiang Silicon Material or generate 5.34% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Jinsanjiang Silicon Material vs. Guizhou BroadcastingTV Info
Performance |
Timeline |
Jinsanjiang Silicon |
Guizhou BroadcastingTV |
Jinsanjiang Silicon and Guizhou BroadcastingTV Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Jinsanjiang Silicon and Guizhou BroadcastingTV
The main advantage of trading using opposite Jinsanjiang Silicon and Guizhou BroadcastingTV positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Jinsanjiang Silicon position performs unexpectedly, Guizhou BroadcastingTV 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 Guizhou BroadcastingTV will offset losses from the drop in Guizhou BroadcastingTV's long position.Jinsanjiang Silicon vs. Zijin Mining Group | Jinsanjiang Silicon vs. Wanhua Chemical Group | Jinsanjiang Silicon vs. Baoshan Iron Steel | Jinsanjiang Silicon vs. Shandong Gold Mining |
Guizhou BroadcastingTV vs. Lutian Machinery Co | Guizhou BroadcastingTV vs. PetroChina Co Ltd | Guizhou BroadcastingTV vs. Bank of China | Guizhou BroadcastingTV vs. China Citic Bank |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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