Correlation Between Turkiye Is and SASA Polyester
Can any of the company-specific risk be diversified away by investing in both Turkiye Is and SASA Polyester 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 Is and SASA Polyester into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Turkiye Is Bankasi and SASA Polyester Sanayi, you can compare the effects of market volatilities on Turkiye Is and SASA Polyester 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 Is with a short position of SASA Polyester. Check out your portfolio center. Please also check ongoing floating volatility patterns of Turkiye Is and SASA Polyester.
Diversification Opportunities for Turkiye Is and SASA Polyester
0.71 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Turkiye and SASA is 0.71. Overlapping area represents the amount of risk that can be diversified away by holding Turkiye Is Bankasi and SASA Polyester Sanayi in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SASA Polyester Sanayi and Turkiye Is 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 Is Bankasi are associated (or correlated) with SASA Polyester. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SASA Polyester Sanayi has no effect on the direction of Turkiye Is i.e., Turkiye Is and SASA Polyester go up and down completely randomly.
Pair Corralation between Turkiye Is and SASA Polyester
Assuming the 90 days trading horizon Turkiye Is Bankasi is expected to generate 1.06 times more return on investment than SASA Polyester. However, Turkiye Is is 1.06 times more volatile than SASA Polyester Sanayi. It trades about 0.26 of its potential returns per unit of risk. SASA Polyester Sanayi is currently generating about 0.16 per unit of risk. If you would invest 1,179 in Turkiye Is Bankasi on August 27, 2024 and sell it today you would earn a total of 171.00 from holding Turkiye Is Bankasi or generate 14.5% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Turkiye Is Bankasi vs. SASA Polyester Sanayi
Performance |
| Timeline |
| Turkiye Is Bankasi |
| SASA Polyester Sanayi |
Turkiye Is and SASA Polyester Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Turkiye Is and SASA Polyester
The main advantage of trading using opposite Turkiye Is and SASA Polyester positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Turkiye Is position performs unexpectedly, SASA Polyester 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 SASA Polyester will offset losses from the drop in SASA Polyester's long position.| Turkiye Is vs. Turkiye Garanti Bankasi | Turkiye Is vs. Akbank TAS | Turkiye Is vs. Yapi ve Kredi | Turkiye Is vs. Turkiye Sise ve |
| SASA Polyester vs. Qnb Finansbank AS | SASA Polyester vs. QNB Finans Finansal | SASA Polyester vs. Turkiye Kalkinma Bankasi | SASA Polyester vs. Kocaer Celik Sanayi |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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