Correlation Between 2G ENERGY and Cass Information
Can any of the company-specific risk be diversified away by investing in both 2G ENERGY and Cass Information 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 2G ENERGY and Cass Information into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between 2G ENERGY and Cass Information Systems, you can compare the effects of market volatilities on 2G ENERGY and Cass Information 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 2G ENERGY with a short position of Cass Information. Check out your portfolio center. Please also check ongoing floating volatility patterns of 2G ENERGY and Cass Information.
Diversification Opportunities for 2G ENERGY and Cass Information
-0.65 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between 2GB and Cass is -0.65. Overlapping area represents the amount of risk that can be diversified away by holding 2G ENERGY and Cass Information Systems in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Cass Information Systems and 2G ENERGY 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 2G ENERGY are associated (or correlated) with Cass Information. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Cass Information Systems has no effect on the direction of 2G ENERGY i.e., 2G ENERGY and Cass Information go up and down completely randomly.
Pair Corralation between 2G ENERGY and Cass Information
Assuming the 90 days trading horizon 2G ENERGY is expected to under-perform the Cass Information. In addition to that, 2G ENERGY is 1.42 times more volatile than Cass Information Systems. It trades about -0.1 of its total potential returns per unit of risk. Cass Information Systems is currently generating about 0.17 per unit of volatility. If you would invest 3,920 in Cass Information Systems on November 28, 2024 and sell it today you would earn a total of 200.00 from holding Cass Information Systems or generate 5.1% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 95.65% |
| Values | Daily Returns |
2G ENERGY vs. Cass Information Systems
Performance |
| Timeline |
| 2G ENERGY |
| Cass Information Systems |
2G ENERGY and Cass Information Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with 2G ENERGY and Cass Information
The main advantage of trading using opposite 2G ENERGY and Cass Information positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if 2G ENERGY position performs unexpectedly, Cass Information 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 Cass Information will offset losses from the drop in Cass Information's long position.| 2G ENERGY vs. COFCO Joycome Foods | 2G ENERGY vs. Axfood AB | 2G ENERGY vs. SLR Investment Corp | 2G ENERGY vs. CONAGRA FOODS |
| Cass Information vs. ALTAIR RES INC | Cass Information vs. RYANAIR HLDGS ADR | Cass Information vs. COSTCO WHOLESALE CDR | Cass Information vs. SPARTAN STORES |
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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