Correlation Between Borlease Otomotiv and Cemtas Celik
Can any of the company-specific risk be diversified away by investing in both Borlease Otomotiv and Cemtas Celik 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 Borlease Otomotiv and Cemtas Celik into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Borlease Otomotiv AS and Cemtas Celik Makina, you can compare the effects of market volatilities on Borlease Otomotiv and Cemtas Celik 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 Borlease Otomotiv with a short position of Cemtas Celik. Check out your portfolio center. Please also check ongoing floating volatility patterns of Borlease Otomotiv and Cemtas Celik.
Diversification Opportunities for Borlease Otomotiv and Cemtas Celik
0.62 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Borlease and Cemtas is 0.62. Overlapping area represents the amount of risk that can be diversified away by holding Borlease Otomotiv AS and Cemtas Celik Makina in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Cemtas Celik Makina and Borlease Otomotiv 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 Borlease Otomotiv AS are associated (or correlated) with Cemtas Celik. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Cemtas Celik Makina has no effect on the direction of Borlease Otomotiv i.e., Borlease Otomotiv and Cemtas Celik go up and down completely randomly.
Pair Corralation between Borlease Otomotiv and Cemtas Celik
Assuming the 90 days trading horizon Borlease Otomotiv AS is expected to generate 1.21 times more return on investment than Cemtas Celik. However, Borlease Otomotiv is 1.21 times more volatile than Cemtas Celik Makina. It trades about 0.21 of its potential returns per unit of risk. Cemtas Celik Makina is currently generating about 0.04 per unit of risk. If you would invest 6,695 in Borlease Otomotiv AS on December 26, 2024 and sell it today you would earn a total of 2,765 from holding Borlease Otomotiv AS or generate 41.3% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Borlease Otomotiv AS vs. Cemtas Celik Makina
Performance |
Timeline |
Borlease Otomotiv |
Cemtas Celik Makina |
Borlease Otomotiv and Cemtas Celik Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Borlease Otomotiv and Cemtas Celik
The main advantage of trading using opposite Borlease Otomotiv and Cemtas Celik positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Borlease Otomotiv position performs unexpectedly, Cemtas Celik 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 Cemtas Celik will offset losses from the drop in Cemtas Celik's long position.Borlease Otomotiv vs. E Data Teknoloji Pazarlama | Borlease Otomotiv vs. Creditwest Faktoring AS | Borlease Otomotiv vs. Sodas Sodyum Sanayi | Borlease Otomotiv 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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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