Correlation Between SENECA FOODS-A and Zhejiang Expressway
Can any of the company-specific risk be diversified away by investing in both SENECA FOODS-A and Zhejiang Expressway 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 SENECA FOODS-A and Zhejiang Expressway into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between SENECA FOODS A and Zhejiang Expressway Co, you can compare the effects of market volatilities on SENECA FOODS-A and Zhejiang Expressway 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 SENECA FOODS-A with a short position of Zhejiang Expressway. Check out your portfolio center. Please also check ongoing floating volatility patterns of SENECA FOODS-A and Zhejiang Expressway.
Diversification Opportunities for SENECA FOODS-A and Zhejiang Expressway
0.12 | Correlation Coefficient |
Average diversification
The 3 months correlation between SENECA and Zhejiang is 0.12. Overlapping area represents the amount of risk that can be diversified away by holding SENECA FOODS A and Zhejiang Expressway Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Zhejiang Expressway and SENECA FOODS-A 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 SENECA FOODS A are associated (or correlated) with Zhejiang Expressway. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Zhejiang Expressway has no effect on the direction of SENECA FOODS-A i.e., SENECA FOODS-A and Zhejiang Expressway go up and down completely randomly.
Pair Corralation between SENECA FOODS-A and Zhejiang Expressway
Assuming the 90 days trading horizon SENECA FOODS A is expected to generate 1.34 times more return on investment than Zhejiang Expressway. However, SENECA FOODS-A is 1.34 times more volatile than Zhejiang Expressway Co. It trades about 0.24 of its potential returns per unit of risk. Zhejiang Expressway Co is currently generating about 0.07 per unit of risk. If you would invest 5,450 in SENECA FOODS A on October 9, 2024 and sell it today you would earn a total of 1,900 from holding SENECA FOODS A or generate 34.86% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
SENECA FOODS A vs. Zhejiang Expressway Co
Performance |
Timeline |
SENECA FOODS A |
Zhejiang Expressway |
SENECA FOODS-A and Zhejiang Expressway Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with SENECA FOODS-A and Zhejiang Expressway
The main advantage of trading using opposite SENECA FOODS-A and Zhejiang Expressway positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SENECA FOODS-A position performs unexpectedly, Zhejiang Expressway 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 Zhejiang Expressway will offset losses from the drop in Zhejiang Expressway's long position.SENECA FOODS-A vs. KENEDIX OFFICE INV | SENECA FOODS-A vs. Xinhua Winshare Publishing | SENECA FOODS-A vs. Laureate Education | SENECA FOODS-A vs. DEVRY EDUCATION GRP |
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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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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