Correlation Between Platform Turizm and Lokman Hekim
Can any of the company-specific risk be diversified away by investing in both Platform Turizm and Lokman Hekim 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 Platform Turizm and Lokman Hekim into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Platform Turizm Tasimacilik and Lokman Hekim Engurusag, you can compare the effects of market volatilities on Platform Turizm and Lokman Hekim 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 Platform Turizm with a short position of Lokman Hekim. Check out your portfolio center. Please also check ongoing floating volatility patterns of Platform Turizm and Lokman Hekim.
Diversification Opportunities for Platform Turizm and Lokman Hekim
0.7 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Platform and Lokman is 0.7. Overlapping area represents the amount of risk that can be diversified away by holding Platform Turizm Tasimacilik and Lokman Hekim Engurusag in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Lokman Hekim Engurusag and Platform Turizm 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 Platform Turizm Tasimacilik are associated (or correlated) with Lokman Hekim. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Lokman Hekim Engurusag has no effect on the direction of Platform Turizm i.e., Platform Turizm and Lokman Hekim go up and down completely randomly.
Pair Corralation between Platform Turizm and Lokman Hekim
Assuming the 90 days trading horizon Platform Turizm Tasimacilik is expected to generate 2.64 times more return on investment than Lokman Hekim. However, Platform Turizm is 2.64 times more volatile than Lokman Hekim Engurusag. It trades about 0.39 of its potential returns per unit of risk. Lokman Hekim Engurusag is currently generating about -0.19 per unit of risk. If you would invest 2,588 in Platform Turizm Tasimacilik on September 25, 2024 and sell it today you would earn a total of 724.00 from holding Platform Turizm Tasimacilik or generate 27.98% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Platform Turizm Tasimacilik vs. Lokman Hekim Engurusag
Performance |
Timeline |
Platform Turizm Tasi |
Lokman Hekim Engurusag |
Platform Turizm and Lokman Hekim Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Platform Turizm and Lokman Hekim
The main advantage of trading using opposite Platform Turizm and Lokman Hekim positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Platform Turizm position performs unexpectedly, Lokman Hekim 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 Lokman Hekim will offset losses from the drop in Lokman Hekim's long position.Platform Turizm vs. Ufuk Yatirim Yonetim | Platform Turizm vs. Beyaz Filo Oto | Platform Turizm vs. Vakif Finansal Kiralama | Platform Turizm vs. Gentas Genel Metal |
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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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