Correlation Between Kofola CeskoSlovensko and CTP NV
Can any of the company-specific risk be diversified away by investing in both Kofola CeskoSlovensko and CTP NV 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 Kofola CeskoSlovensko and CTP NV into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Kofola CeskoSlovensko as and CTP NV, you can compare the effects of market volatilities on Kofola CeskoSlovensko and CTP NV 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 Kofola CeskoSlovensko with a short position of CTP NV. Check out your portfolio center. Please also check ongoing floating volatility patterns of Kofola CeskoSlovensko and CTP NV.
Diversification Opportunities for Kofola CeskoSlovensko and CTP NV
-0.76 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Kofola and CTP is -0.76. Overlapping area represents the amount of risk that can be diversified away by holding Kofola CeskoSlovensko as and CTP NV in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CTP NV and Kofola CeskoSlovensko 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 Kofola CeskoSlovensko as are associated (or correlated) with CTP NV. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CTP NV has no effect on the direction of Kofola CeskoSlovensko i.e., Kofola CeskoSlovensko and CTP NV go up and down completely randomly.
Pair Corralation between Kofola CeskoSlovensko and CTP NV
Assuming the 90 days trading horizon Kofola CeskoSlovensko as is expected to generate 0.59 times more return on investment than CTP NV. However, Kofola CeskoSlovensko as is 1.69 times less risky than CTP NV. It trades about 0.34 of its potential returns per unit of risk. CTP NV is currently generating about -0.09 per unit of risk. If you would invest 32,159 in Kofola CeskoSlovensko as on September 19, 2024 and sell it today you would earn a total of 6,741 from holding Kofola CeskoSlovensko as or generate 20.96% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 98.44% |
Values | Daily Returns |
Kofola CeskoSlovensko as vs. CTP NV
Performance |
Timeline |
Kofola CeskoSlovensko |
CTP NV |
Kofola CeskoSlovensko and CTP NV Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Kofola CeskoSlovensko and CTP NV
The main advantage of trading using opposite Kofola CeskoSlovensko and CTP NV positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Kofola CeskoSlovensko position performs unexpectedly, CTP NV 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 CTP NV will offset losses from the drop in CTP NV's long position.Kofola CeskoSlovensko vs. Moneta Money Bank | Kofola CeskoSlovensko vs. Komercni Banka AS | Kofola CeskoSlovensko vs. Cez AS | Kofola CeskoSlovensko vs. Erste Group Bank |
CTP NV vs. UNIQA Insurance Group | CTP NV vs. Raiffeisen Bank International | CTP NV vs. Vienna Insurance Group | CTP NV vs. Komercni Banka AS |
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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