Correlation Between Save Foods and Origin Agritech
Can any of the company-specific risk be diversified away by investing in both Save Foods and Origin Agritech 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 Save Foods and Origin Agritech into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Save Foods and Origin Agritech, you can compare the effects of market volatilities on Save Foods and Origin Agritech 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 Save Foods with a short position of Origin Agritech. Check out your portfolio center. Please also check ongoing floating volatility patterns of Save Foods and Origin Agritech.
Diversification Opportunities for Save Foods and Origin Agritech
0.15 | Correlation Coefficient |
Average diversification
The 3 months correlation between Save and Origin is 0.15. Overlapping area represents the amount of risk that can be diversified away by holding Save Foods and Origin Agritech in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Origin Agritech and Save Foods 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 Save Foods are associated (or correlated) with Origin Agritech. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Origin Agritech has no effect on the direction of Save Foods i.e., Save Foods and Origin Agritech go up and down completely randomly.
Pair Corralation between Save Foods and Origin Agritech
Given the investment horizon of 90 days Save Foods is expected to generate 1.19 times more return on investment than Origin Agritech. However, Save Foods is 1.19 times more volatile than Origin Agritech. It trades about 0.0 of its potential returns per unit of risk. Origin Agritech is currently generating about -0.01 per unit of risk. If you would invest 83.00 in Save Foods on September 2, 2024 and sell it today you would lose (24.00) from holding Save Foods or give up 28.92% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 30.85% |
| Values | Daily Returns |
Save Foods vs. Origin Agritech
Performance |
| Timeline |
| Save Foods |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
| Origin Agritech |
Save Foods and Origin Agritech Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Save Foods and Origin Agritech
The main advantage of trading using opposite Save Foods and Origin Agritech positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Save Foods position performs unexpectedly, Origin Agritech 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 Origin Agritech will offset losses from the drop in Origin Agritech's long position.| Save Foods vs. Origin Agritech | Save Foods vs. Benson Hill, Common | Save Foods vs. Corteva | Save Foods vs. Scotts Miracle Gro |
| Origin Agritech vs. Benson Hill, Common | Origin Agritech vs. Corteva | Origin Agritech vs. Scotts Miracle Gro | Origin Agritech vs. Yara International ASA |
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 Correlation Analysis module to reduce portfolio risk simply by holding instruments which are not perfectly correlated.
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