Correlation Between Kardemir Karabuk and Ford Otomotiv
Can any of the company-specific risk be diversified away by investing in both Kardemir Karabuk and Ford Otomotiv 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 Kardemir Karabuk and Ford Otomotiv into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Kardemir Karabuk Demir and Ford Otomotiv Sanayi, you can compare the effects of market volatilities on Kardemir Karabuk and Ford Otomotiv 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 Kardemir Karabuk with a short position of Ford Otomotiv. Check out your portfolio center. Please also check ongoing floating volatility patterns of Kardemir Karabuk and Ford Otomotiv.
Diversification Opportunities for Kardemir Karabuk and Ford Otomotiv
0.11 | Correlation Coefficient |
Average diversification
The 3 months correlation between Kardemir and Ford is 0.11. Overlapping area represents the amount of risk that can be diversified away by holding Kardemir Karabuk Demir and Ford Otomotiv Sanayi in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ford Otomotiv Sanayi and Kardemir Karabuk 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 Kardemir Karabuk Demir are associated (or correlated) with Ford Otomotiv. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ford Otomotiv Sanayi has no effect on the direction of Kardemir Karabuk i.e., Kardemir Karabuk and Ford Otomotiv go up and down completely randomly.
Pair Corralation between Kardemir Karabuk and Ford Otomotiv
Assuming the 90 days trading horizon Kardemir Karabuk is expected to generate 1.26 times less return on investment than Ford Otomotiv. In addition to that, Kardemir Karabuk is 1.3 times more volatile than Ford Otomotiv Sanayi. It trades about 0.05 of its total potential returns per unit of risk. Ford Otomotiv Sanayi is currently generating about 0.07 per unit of volatility. If you would invest 43,662 in Ford Otomotiv Sanayi on September 26, 2024 and sell it today you would earn a total of 49,588 from holding Ford Otomotiv Sanayi or generate 113.57% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 99.8% |
Values | Daily Returns |
Kardemir Karabuk Demir vs. Ford Otomotiv Sanayi
Performance |
Timeline |
Kardemir Karabuk Demir |
Ford Otomotiv Sanayi |
Kardemir Karabuk and Ford Otomotiv Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Kardemir Karabuk and Ford Otomotiv
The main advantage of trading using opposite Kardemir Karabuk and Ford Otomotiv positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Kardemir Karabuk position performs unexpectedly, Ford Otomotiv 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 Ford Otomotiv will offset losses from the drop in Ford Otomotiv's long position.Kardemir Karabuk vs. Ege Endustri ve | Kardemir Karabuk vs. Bosch Fren Sistemleri | Kardemir Karabuk vs. Dogus Otomotiv Servis | Kardemir Karabuk vs. Nuh Cimento 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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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