Correlation Between Tofas Turk and Borusan Yatirim
Can any of the company-specific risk be diversified away by investing in both Tofas Turk and Borusan 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 Tofas Turk and Borusan Yatirim into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Tofas Turk Otomobil and Borusan Yatirim ve, you can compare the effects of market volatilities on Tofas Turk and Borusan 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 Tofas Turk with a short position of Borusan Yatirim. Check out your portfolio center. Please also check ongoing floating volatility patterns of Tofas Turk and Borusan Yatirim.
Diversification Opportunities for Tofas Turk and Borusan Yatirim
0.33 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Tofas and Borusan is 0.33. Overlapping area represents the amount of risk that can be diversified away by holding Tofas Turk Otomobil and Borusan Yatirim ve in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Borusan Yatirim ve and Tofas Turk 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 Tofas Turk Otomobil are associated (or correlated) with Borusan Yatirim. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Borusan Yatirim ve has no effect on the direction of Tofas Turk i.e., Tofas Turk and Borusan Yatirim go up and down completely randomly.
Pair Corralation between Tofas Turk and Borusan Yatirim
Assuming the 90 days trading horizon Tofas Turk Otomobil is expected to under-perform the Borusan Yatirim. In addition to that, Tofas Turk is 1.05 times more volatile than Borusan Yatirim ve. It trades about -0.22 of its total potential returns per unit of risk. Borusan Yatirim ve is currently generating about 0.28 per unit of volatility. If you would invest 199,800 in Borusan Yatirim ve on September 23, 2024 and sell it today you would earn a total of 24,200 from holding Borusan Yatirim ve or generate 12.11% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Tofas Turk Otomobil vs. Borusan Yatirim ve
Performance |
Timeline |
Tofas Turk Otomobil |
Borusan Yatirim ve |
Tofas Turk and Borusan Yatirim Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Tofas Turk and Borusan Yatirim
The main advantage of trading using opposite Tofas Turk and Borusan Yatirim positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Tofas Turk position performs unexpectedly, Borusan 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 Borusan Yatirim will offset losses from the drop in Borusan Yatirim's long position.Tofas Turk vs. Ford Otomotiv Sanayi | Tofas Turk vs. Hektas Ticaret TAS | Tofas Turk vs. Eregli Demir ve | Tofas Turk vs. Aksa Akrilik Kimya |
Borusan Yatirim vs. Aksa Akrilik Kimya | Borusan Yatirim vs. Tofas Turk Otomobil | Borusan Yatirim vs. AK Sigorta AS | Borusan Yatirim vs. Is Yatirim Menkul |
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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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