Correlation Between Turkiye Garanti and Turk Prysmian
Can any of the company-specific risk be diversified away by investing in both Turkiye Garanti and Turk Prysmian 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 Turkiye Garanti and Turk Prysmian into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Turkiye Garanti Bankasi and Turk Prysmian Kablo, you can compare the effects of market volatilities on Turkiye Garanti and Turk Prysmian 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 Turkiye Garanti with a short position of Turk Prysmian. Check out your portfolio center. Please also check ongoing floating volatility patterns of Turkiye Garanti and Turk Prysmian.
Diversification Opportunities for Turkiye Garanti and Turk Prysmian
-0.05 | Correlation Coefficient |
Good diversification
The 3 months correlation between Turkiye and Turk is -0.05. Overlapping area represents the amount of risk that can be diversified away by holding Turkiye Garanti Bankasi and Turk Prysmian Kablo in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Turk Prysmian Kablo and Turkiye Garanti 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 Turkiye Garanti Bankasi are associated (or correlated) with Turk Prysmian. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Turk Prysmian Kablo has no effect on the direction of Turkiye Garanti i.e., Turkiye Garanti and Turk Prysmian go up and down completely randomly.
Pair Corralation between Turkiye Garanti and Turk Prysmian
Assuming the 90 days trading horizon Turkiye Garanti Bankasi is expected to generate 1.29 times more return on investment than Turk Prysmian. However, Turkiye Garanti is 1.29 times more volatile than Turk Prysmian Kablo. It trades about -0.08 of its potential returns per unit of risk. Turk Prysmian Kablo is currently generating about -0.11 per unit of risk. If you would invest 12,540 in Turkiye Garanti Bankasi on December 22, 2024 and sell it today you would lose (1,820) from holding Turkiye Garanti Bankasi or give up 14.51% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Turkiye Garanti Bankasi vs. Turk Prysmian Kablo
Performance |
Timeline |
Turkiye Garanti Bankasi |
Turk Prysmian Kablo |
Turkiye Garanti and Turk Prysmian Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Turkiye Garanti and Turk Prysmian
The main advantage of trading using opposite Turkiye Garanti and Turk Prysmian positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Turkiye Garanti position performs unexpectedly, Turk Prysmian 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 Turk Prysmian will offset losses from the drop in Turk Prysmian's long position.Turkiye Garanti vs. Akbank TAS | Turkiye Garanti vs. Turkiye Is Bankasi | Turkiye Garanti vs. Yapi ve Kredi | Turkiye Garanti vs. Turkish Airlines |
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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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