Correlation Between Dogus Gayrimenkul and Kafein Yazilim
Can any of the company-specific risk be diversified away by investing in both Dogus Gayrimenkul and Kafein Yazilim 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 Dogus Gayrimenkul and Kafein Yazilim into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Dogus Gayrimenkul Yatirim and Kafein Yazilim, you can compare the effects of market volatilities on Dogus Gayrimenkul and Kafein Yazilim 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 Dogus Gayrimenkul with a short position of Kafein Yazilim. Check out your portfolio center. Please also check ongoing floating volatility patterns of Dogus Gayrimenkul and Kafein Yazilim.
Diversification Opportunities for Dogus Gayrimenkul and Kafein Yazilim
-0.35 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Dogus and Kafein is -0.35. Overlapping area represents the amount of risk that can be diversified away by holding Dogus Gayrimenkul Yatirim and Kafein Yazilim in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kafein Yazilim and Dogus Gayrimenkul 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 Dogus Gayrimenkul Yatirim are associated (or correlated) with Kafein Yazilim. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kafein Yazilim has no effect on the direction of Dogus Gayrimenkul i.e., Dogus Gayrimenkul and Kafein Yazilim go up and down completely randomly.
Pair Corralation between Dogus Gayrimenkul and Kafein Yazilim
Assuming the 90 days trading horizon Dogus Gayrimenkul Yatirim is expected to generate 0.87 times more return on investment than Kafein Yazilim. However, Dogus Gayrimenkul Yatirim is 1.15 times less risky than Kafein Yazilim. It trades about 0.29 of its potential returns per unit of risk. Kafein Yazilim is currently generating about -0.1 per unit of risk. If you would invest 3,278 in Dogus Gayrimenkul Yatirim on August 31, 2024 and sell it today you would earn a total of 740.00 from holding Dogus Gayrimenkul Yatirim or generate 22.57% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Dogus Gayrimenkul Yatirim vs. Kafein Yazilim
Performance |
| Timeline |
| Dogus Gayrimenkul Yatirim |
| Kafein Yazilim |
Dogus Gayrimenkul and Kafein Yazilim Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Dogus Gayrimenkul and Kafein Yazilim
The main advantage of trading using opposite Dogus Gayrimenkul and Kafein Yazilim positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Dogus Gayrimenkul position performs unexpectedly, Kafein Yazilim 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 Kafein Yazilim will offset losses from the drop in Kafein Yazilim's long position.| Dogus Gayrimenkul vs. MEGA METAL | Dogus Gayrimenkul vs. Gentas Genel Metal | Dogus Gayrimenkul vs. Politeknik Metal Sanayi | Dogus Gayrimenkul vs. Bms Birlesik 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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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