Correlation Between Great Wall and Standard Foods
Can any of the company-specific risk be diversified away by investing in both Great Wall and Standard Foods at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining Great Wall and Standard Foods into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Great Wall Enterprise and Standard Foods Corp, you can compare the effects of market volatilities on Great Wall and Standard Foods 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 Great Wall with a short position of Standard Foods. Check out your portfolio center. Please also check ongoing floating volatility patterns of Great Wall and Standard Foods.
Diversification Opportunities for Great Wall and Standard Foods
0.31 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Great and Standard is 0.31. Overlapping area represents the amount of risk that can be diversified away by holding Great Wall Enterprise and Standard Foods Corp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Standard Foods Corp and Great Wall 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 Great Wall Enterprise are associated (or correlated) with Standard Foods. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Standard Foods Corp has no effect on the direction of Great Wall i.e., Great Wall and Standard Foods go up and down completely randomly.
Pair Corralation between Great Wall and Standard Foods
Assuming the 90 days trading horizon Great Wall Enterprise is expected to generate 1.03 times more return on investment than Standard Foods. However, Great Wall is 1.03 times more volatile than Standard Foods Corp. It trades about 0.38 of its potential returns per unit of risk. Standard Foods Corp is currently generating about 0.07 per unit of risk. If you would invest 5,110 in Great Wall Enterprise on August 28, 2024 and sell it today you would earn a total of 230.00 from holding Great Wall Enterprise or generate 4.5% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Great Wall Enterprise vs. Standard Foods Corp
Performance |
| Timeline |
| Great Wall Enterprise |
| Standard Foods Corp |
Great Wall and Standard Foods Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Great Wall and Standard Foods
The main advantage of trading using opposite Great Wall and Standard Foods positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Great Wall position performs unexpectedly, Standard Foods 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 Standard Foods will offset losses from the drop in Standard Foods' long position.| Great Wall vs. Taiwan Cement Corp | Great Wall vs. Ruentex Development Co | Great Wall vs. Symtek Automation Asia | Great Wall vs. CTCI Corp |
| Standard Foods vs. Taiwan Cement Corp | Standard Foods vs. Ruentex Development Co | Standard Foods vs. Symtek Automation Asia | Standard Foods vs. CTCI Corp |
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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