Correlation Between GSD Holding and Yesil Yatirim
Can any of the company-specific risk be diversified away by investing in both GSD Holding and Yesil Yatirim 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 GSD Holding and Yesil Yatirim into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between GSD Holding AS and Yesil Yatirim Holding, you can compare the effects of market volatilities on GSD Holding and Yesil Yatirim 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 GSD Holding with a short position of Yesil Yatirim. Check out your portfolio center. Please also check ongoing floating volatility patterns of GSD Holding and Yesil Yatirim.
Diversification Opportunities for GSD Holding and Yesil Yatirim
0.73 | Correlation Coefficient |
Poor diversification
The 3 months correlation between GSD and Yesil is 0.73. Overlapping area represents the amount of risk that can be diversified away by holding GSD Holding AS and Yesil Yatirim Holding in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Yesil Yatirim Holding and GSD Holding 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 GSD Holding AS are associated (or correlated) with Yesil Yatirim. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Yesil Yatirim Holding has no effect on the direction of GSD Holding i.e., GSD Holding and Yesil Yatirim go up and down completely randomly.
Pair Corralation between GSD Holding and Yesil Yatirim
Assuming the 90 days trading horizon GSD Holding is expected to generate 2.8 times less return on investment than Yesil Yatirim. But when comparing it to its historical volatility, GSD Holding AS is 2.87 times less risky than Yesil Yatirim. It trades about 0.34 of its potential returns per unit of risk. Yesil Yatirim Holding is currently generating about 0.33 of returns per unit of risk over similar time horizon. If you would invest 128.00 in Yesil Yatirim Holding on September 13, 2024 and sell it today you would earn a total of 98.00 from holding Yesil Yatirim Holding or generate 76.56% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 97.67% |
| Values | Daily Returns |
GSD Holding AS vs. Yesil Yatirim Holding
Performance |
| Timeline |
| GSD Holding AS |
| Yesil Yatirim Holding |
GSD Holding and Yesil Yatirim Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with GSD Holding and Yesil Yatirim
The main advantage of trading using opposite GSD Holding and Yesil Yatirim positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GSD Holding position performs unexpectedly, Yesil Yatirim 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 Yesil Yatirim will offset losses from the drop in Yesil Yatirim's long position.| GSD Holding vs. Pamel Yenilenebilir Elektrik | GSD Holding vs. Bosch Fren Sistemleri | GSD Holding vs. Marka Yatirim Holding | GSD Holding vs. Dogus Gayrimenkul Yatirim |
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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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