Correlation Between Tumosan and Creditwest Faktoring
Can any of the company-specific risk be diversified away by investing in both Tumosan and Creditwest Faktoring 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 Tumosan and Creditwest Faktoring into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Tumosan Motor ve and Creditwest Faktoring AS, you can compare the effects of market volatilities on Tumosan and Creditwest Faktoring 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 Tumosan with a short position of Creditwest Faktoring. Check out your portfolio center. Please also check ongoing floating volatility patterns of Tumosan and Creditwest Faktoring.
Diversification Opportunities for Tumosan and Creditwest Faktoring
-0.02 | Correlation Coefficient |
Good diversification
The 3 months correlation between Tumosan and Creditwest is -0.02. Overlapping area represents the amount of risk that can be diversified away by holding Tumosan Motor ve and Creditwest Faktoring AS in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Creditwest Faktoring and Tumosan 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 Tumosan Motor ve are associated (or correlated) with Creditwest Faktoring. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Creditwest Faktoring has no effect on the direction of Tumosan i.e., Tumosan and Creditwest Faktoring go up and down completely randomly.
Pair Corralation between Tumosan and Creditwest Faktoring
Assuming the 90 days trading horizon Tumosan Motor ve is expected to under-perform the Creditwest Faktoring. But the stock apears to be less risky and, when comparing its historical volatility, Tumosan Motor ve is 1.12 times less risky than Creditwest Faktoring. The stock trades about -0.08 of its potential returns per unit of risk. The Creditwest Faktoring AS is currently generating about -0.02 of returns per unit of risk over similar time horizon. If you would invest 825.00 in Creditwest Faktoring AS on September 3, 2024 and sell it today you would lose (109.00) from holding Creditwest Faktoring AS or give up 13.21% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Tumosan Motor ve vs. Creditwest Faktoring AS
Performance |
Timeline |
Tumosan Motor ve |
Creditwest Faktoring |
Tumosan and Creditwest Faktoring Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Tumosan and Creditwest Faktoring
The main advantage of trading using opposite Tumosan and Creditwest Faktoring positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Tumosan position performs unexpectedly, Creditwest Faktoring 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 Creditwest Faktoring will offset losses from the drop in Creditwest Faktoring's long position.Tumosan vs. Politeknik Metal Sanayi | Tumosan vs. Akbank TAS | Tumosan vs. Turkiye Kalkinma Bankasi | Tumosan vs. Koza Anadolu 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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