Correlation Between Bms Birlesik and Koza Polyester
Can any of the company-specific risk be diversified away by investing in both Bms Birlesik and Koza 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 Bms Birlesik and Koza Polyester into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Bms Birlesik Metal and Koza Polyester Sanayi, you can compare the effects of market volatilities on Bms Birlesik and Koza 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 Bms Birlesik with a short position of Koza Polyester. Check out your portfolio center. Please also check ongoing floating volatility patterns of Bms Birlesik and Koza Polyester.
Diversification Opportunities for Bms Birlesik and Koza Polyester
0.46 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Bms and Koza is 0.46. Overlapping area represents the amount of risk that can be diversified away by holding Bms Birlesik Metal and Koza Polyester Sanayi in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Koza Polyester Sanayi and Bms Birlesik 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 Bms Birlesik Metal are associated (or correlated) with Koza Polyester. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Koza Polyester Sanayi has no effect on the direction of Bms Birlesik i.e., Bms Birlesik and Koza Polyester go up and down completely randomly.
Pair Corralation between Bms Birlesik and Koza Polyester
Assuming the 90 days trading horizon Bms Birlesik is expected to generate 3.21 times less return on investment than Koza Polyester. In addition to that, Bms Birlesik is 1.24 times more volatile than Koza Polyester Sanayi. It trades about 0.06 of its total potential returns per unit of risk. Koza Polyester Sanayi is currently generating about 0.26 per unit of volatility. If you would invest 556.00 in Koza Polyester Sanayi on September 22, 2024 and sell it today you would earn a total of 78.00 from holding Koza Polyester Sanayi or generate 14.03% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Bms Birlesik Metal vs. Koza Polyester Sanayi
Performance |
Timeline |
Bms Birlesik Metal |
Koza Polyester Sanayi |
Bms Birlesik and Koza Polyester Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Bms Birlesik and Koza Polyester
The main advantage of trading using opposite Bms Birlesik and Koza Polyester positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Bms Birlesik position performs unexpectedly, Koza 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 Koza Polyester will offset losses from the drop in Koza Polyester's long position.Bms Birlesik vs. Eregli Demir ve | Bms Birlesik vs. Iskenderun Demir ve | Bms Birlesik vs. Kardemir Karabuk Demir | Bms Birlesik vs. Dogus Gayrimenkul Yatirim |
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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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