Correlation Between Fangda Special and Guangdong Wens
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By analyzing existing cross correlation between Fangda Special Steel and Guangdong Wens Foodstuff, you can compare the effects of market volatilities on Fangda Special and Guangdong Wens 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 Fangda Special with a short position of Guangdong Wens. Check out your portfolio center. Please also check ongoing floating volatility patterns of Fangda Special and Guangdong Wens.
Diversification Opportunities for Fangda Special and Guangdong Wens
0.77 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Fangda and Guangdong is 0.77. Overlapping area represents the amount of risk that can be diversified away by holding Fangda Special Steel and Guangdong Wens Foodstuff in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Guangdong Wens Foodstuff and Fangda Special 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 Fangda Special Steel are associated (or correlated) with Guangdong Wens. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Guangdong Wens Foodstuff has no effect on the direction of Fangda Special i.e., Fangda Special and Guangdong Wens go up and down completely randomly.
Pair Corralation between Fangda Special and Guangdong Wens
Assuming the 90 days trading horizon Fangda Special Steel is expected to generate 2.92 times more return on investment than Guangdong Wens. However, Fangda Special is 2.92 times more volatile than Guangdong Wens Foodstuff. It trades about 0.08 of its potential returns per unit of risk. Guangdong Wens Foodstuff is currently generating about -0.06 per unit of risk. If you would invest 399.00 in Fangda Special Steel on November 7, 2024 and sell it today you would earn a total of 15.00 from holding Fangda Special Steel or generate 3.76% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Fangda Special Steel vs. Guangdong Wens Foodstuff
Performance |
| Timeline |
| Fangda Special Steel |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
| Guangdong Wens Foodstuff |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
Fangda Special and Guangdong Wens Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Fangda Special and Guangdong Wens
The main advantage of trading using opposite Fangda Special and Guangdong Wens positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Fangda Special position performs unexpectedly, Guangdong Wens 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 Guangdong Wens will offset losses from the drop in Guangdong Wens' long position.The idea behind Fangda Special Steel and Guangdong Wens Foodstuff 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 Volatility Analysis module to get historical volatility and risk analysis based on latest market data.
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