Correlation Between IPG Photonics and Eurobank Ergasias
Can any of the company-specific risk be diversified away by investing in both IPG Photonics and Eurobank Ergasias 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 IPG Photonics and Eurobank Ergasias into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between IPG Photonics and Eurobank Ergasias Services, you can compare the effects of market volatilities on IPG Photonics and Eurobank Ergasias 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 IPG Photonics with a short position of Eurobank Ergasias. Check out your portfolio center. Please also check ongoing floating volatility patterns of IPG Photonics and Eurobank Ergasias.
Diversification Opportunities for IPG Photonics and Eurobank Ergasias
-0.1 | Correlation Coefficient |
Good diversification
The 3 months correlation between IPG and Eurobank is -0.1. Overlapping area represents the amount of risk that can be diversified away by holding IPG Photonics and Eurobank Ergasias Services in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Eurobank Ergasias and IPG Photonics 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 IPG Photonics are associated (or correlated) with Eurobank Ergasias. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Eurobank Ergasias has no effect on the direction of IPG Photonics i.e., IPG Photonics and Eurobank Ergasias go up and down completely randomly.
Pair Corralation between IPG Photonics and Eurobank Ergasias
Given the investment horizon of 90 days IPG Photonics is expected to under-perform the Eurobank Ergasias. But the stock apears to be less risky and, when comparing its historical volatility, IPG Photonics is 1.09 times less risky than Eurobank Ergasias. The stock trades about -0.19 of its potential returns per unit of risk. The Eurobank Ergasias Services is currently generating about 0.35 of returns per unit of risk over similar time horizon. If you would invest 209.00 in Eurobank Ergasias Services on October 12, 2024 and sell it today you would earn a total of 31.00 from holding Eurobank Ergasias Services or generate 14.83% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
IPG Photonics vs. Eurobank Ergasias Services
Performance |
Timeline |
IPG Photonics |
Eurobank Ergasias |
IPG Photonics and Eurobank Ergasias Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with IPG Photonics and Eurobank Ergasias
The main advantage of trading using opposite IPG Photonics and Eurobank Ergasias positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if IPG Photonics position performs unexpectedly, Eurobank Ergasias 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 Eurobank Ergasias will offset losses from the drop in Eurobank Ergasias' long position.IPG Photonics vs. Teradyne | IPG Photonics vs. Ultra Clean Holdings | IPG Photonics vs. Onto Innovation | IPG Photonics vs. Cohu Inc |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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