Correlation Between Public Power and Thessaloniki Port
Can any of the company-specific risk be diversified away by investing in both Public Power and Thessaloniki Port 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 Public Power and Thessaloniki Port into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Public Power and Thessaloniki Port Authority, you can compare the effects of market volatilities on Public Power and Thessaloniki Port 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 Public Power with a short position of Thessaloniki Port. Check out your portfolio center. Please also check ongoing floating volatility patterns of Public Power and Thessaloniki Port.
Diversification Opportunities for Public Power and Thessaloniki Port
0.5 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Public and Thessaloniki is 0.5. Overlapping area represents the amount of risk that can be diversified away by holding Public Power and Thessaloniki Port Authority in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Thessaloniki Port and Public Power 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 Public Power are associated (or correlated) with Thessaloniki Port. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Thessaloniki Port has no effect on the direction of Public Power i.e., Public Power and Thessaloniki Port go up and down completely randomly.
Pair Corralation between Public Power and Thessaloniki Port
Assuming the 90 days trading horizon Public Power is expected to generate 1.23 times more return on investment than Thessaloniki Port. However, Public Power is 1.23 times more volatile than Thessaloniki Port Authority. It trades about 0.07 of its potential returns per unit of risk. Thessaloniki Port Authority is currently generating about 0.03 per unit of risk. If you would invest 783.00 in Public Power on November 5, 2024 and sell it today you would earn a total of 536.00 from holding Public Power or generate 68.45% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Public Power vs. Thessaloniki Port Authority
Performance |
Timeline |
Public Power |
Thessaloniki Port |
Public Power and Thessaloniki Port Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Public Power and Thessaloniki Port
The main advantage of trading using opposite Public Power and Thessaloniki Port positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Public Power position performs unexpectedly, Thessaloniki Port 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 Thessaloniki Port will offset losses from the drop in Thessaloniki Port's long position.Public Power vs. Mytilineos SA | Public Power vs. Greek Organization of | Public Power vs. Hellenic Telecommunications Organization | Public Power vs. Alpha Services and |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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