Correlation Between Frigoglass SAIC and Autohellas
Can any of the company-specific risk be diversified away by investing in both Frigoglass SAIC and Autohellas 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 Frigoglass SAIC and Autohellas into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Frigoglass SAIC and Autohellas SA, you can compare the effects of market volatilities on Frigoglass SAIC and Autohellas 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 Frigoglass SAIC with a short position of Autohellas. Check out your portfolio center. Please also check ongoing floating volatility patterns of Frigoglass SAIC and Autohellas.
Diversification Opportunities for Frigoglass SAIC and Autohellas
-0.42 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Frigoglass and Autohellas is -0.42. Overlapping area represents the amount of risk that can be diversified away by holding Frigoglass SAIC and Autohellas SA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Autohellas SA and Frigoglass SAIC 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 Frigoglass SAIC are associated (or correlated) with Autohellas. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Autohellas SA has no effect on the direction of Frigoglass SAIC i.e., Frigoglass SAIC and Autohellas go up and down completely randomly.
Pair Corralation between Frigoglass SAIC and Autohellas
Assuming the 90 days trading horizon Frigoglass SAIC is expected to generate 3.13 times more return on investment than Autohellas. However, Frigoglass SAIC is 3.13 times more volatile than Autohellas SA. It trades about -0.03 of its potential returns per unit of risk. Autohellas SA is currently generating about -0.25 per unit of risk. If you would invest 22.00 in Frigoglass SAIC on August 28, 2024 and sell it today you would lose (1.00) from holding Frigoglass SAIC or give up 4.55% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 95.24% |
| Values | Daily Returns |
Frigoglass SAIC vs. Autohellas SA
Performance |
| Timeline |
| Frigoglass SAIC |
| Autohellas SA |
Frigoglass SAIC and Autohellas Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Frigoglass SAIC and Autohellas
The main advantage of trading using opposite Frigoglass SAIC and Autohellas positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Frigoglass SAIC position performs unexpectedly, Autohellas 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 Autohellas will offset losses from the drop in Autohellas' long position.| Frigoglass SAIC vs. Public Power | Frigoglass SAIC vs. Intralot SA Integrated | Frigoglass SAIC vs. Hellenic Petroleum SA | Frigoglass SAIC vs. Mytilineos SA |
| Autohellas vs. Intertech SA Inter | Autohellas vs. Hellenic Telecommunications Organization | Autohellas vs. Profile Systems Software | Autohellas vs. Elton International Trading |
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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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