Correlation Between Euro Menkul and Galatasaray Sportif
Can any of the company-specific risk be diversified away by investing in both Euro Menkul and Galatasaray Sportif 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 Euro Menkul and Galatasaray Sportif into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Euro Menkul Kiymet and Galatasaray Sportif Sinai, you can compare the effects of market volatilities on Euro Menkul and Galatasaray Sportif 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 Euro Menkul with a short position of Galatasaray Sportif. Check out your portfolio center. Please also check ongoing floating volatility patterns of Euro Menkul and Galatasaray Sportif.
Diversification Opportunities for Euro Menkul and Galatasaray Sportif
-0.59 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Euro and Galatasaray is -0.59. Overlapping area represents the amount of risk that can be diversified away by holding Euro Menkul Kiymet and Galatasaray Sportif Sinai in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Galatasaray Sportif Sinai and Euro Menkul 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 Euro Menkul Kiymet are associated (or correlated) with Galatasaray Sportif. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Galatasaray Sportif Sinai has no effect on the direction of Euro Menkul i.e., Euro Menkul and Galatasaray Sportif go up and down completely randomly.
Pair Corralation between Euro Menkul and Galatasaray Sportif
Assuming the 90 days trading horizon Euro Menkul Kiymet is expected to generate 2.51 times more return on investment than Galatasaray Sportif. However, Euro Menkul is 2.51 times more volatile than Galatasaray Sportif Sinai. It trades about 0.3 of its potential returns per unit of risk. Galatasaray Sportif Sinai is currently generating about -0.04 per unit of risk. If you would invest 1,025 in Euro Menkul Kiymet on October 11, 2024 and sell it today you would earn a total of 393.00 from holding Euro Menkul Kiymet or generate 38.34% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 95.45% |
Values | Daily Returns |
Euro Menkul Kiymet vs. Galatasaray Sportif Sinai
Performance |
Timeline |
Euro Menkul Kiymet |
Galatasaray Sportif Sinai |
Euro Menkul and Galatasaray Sportif Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Euro Menkul and Galatasaray Sportif
The main advantage of trading using opposite Euro Menkul and Galatasaray Sportif positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Euro Menkul position performs unexpectedly, Galatasaray Sportif 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 Galatasaray Sportif will offset losses from the drop in Galatasaray Sportif's long position.Euro Menkul vs. Galatasaray Sportif Sinai | Euro Menkul vs. Mackolik Internet Hizmetleri | Euro Menkul vs. Bms Birlesik Metal | Euro Menkul vs. Politeknik Metal Sanayi |
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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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