Correlation Between Klepierre and Carmila SA
Can any of the company-specific risk be diversified away by investing in both Klepierre and Carmila SA 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 Klepierre and Carmila SA into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Klepierre SA and Carmila SA, you can compare the effects of market volatilities on Klepierre and Carmila SA 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 Klepierre with a short position of Carmila SA. Check out your portfolio center. Please also check ongoing floating volatility patterns of Klepierre and Carmila SA.
Diversification Opportunities for Klepierre and Carmila SA
0.7 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Klepierre and Carmila is 0.7. Overlapping area represents the amount of risk that can be diversified away by holding Klepierre SA and Carmila SA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Carmila SA and Klepierre 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 Klepierre SA are associated (or correlated) with Carmila SA. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Carmila SA has no effect on the direction of Klepierre i.e., Klepierre and Carmila SA go up and down completely randomly.
Pair Corralation between Klepierre and Carmila SA
Assuming the 90 days horizon Klepierre SA is expected to generate 0.8 times more return on investment than Carmila SA. However, Klepierre SA is 1.25 times less risky than Carmila SA. It trades about -0.24 of its potential returns per unit of risk. Carmila SA is currently generating about -0.36 per unit of risk. If you would invest 2,980 in Klepierre SA on August 28, 2024 and sell it today you would lose (122.00) from holding Klepierre SA or give up 4.09% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Klepierre SA vs. Carmila SA
Performance |
Timeline |
Klepierre SA |
Carmila SA |
Klepierre and Carmila SA Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Klepierre and Carmila SA
The main advantage of trading using opposite Klepierre and Carmila SA positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Klepierre position performs unexpectedly, Carmila SA 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 Carmila SA will offset losses from the drop in Carmila SA's long position.The idea behind Klepierre SA and Carmila SA pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.Carmila SA vs. Mercialys SA | Carmila SA vs. Icade SA | Carmila SA vs. Klepierre SA | Carmila SA vs. Altarea SCA |
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 Valuation module to check real value of public entities based on technical and fundamental data.
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