Correlation Between Lipum AB and Freemelt Holding
Can any of the company-specific risk be diversified away by investing in both Lipum AB and Freemelt Holding 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 Lipum AB and Freemelt Holding into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Lipum AB and Freemelt Holding AB, you can compare the effects of market volatilities on Lipum AB and Freemelt Holding 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 Lipum AB with a short position of Freemelt Holding. Check out your portfolio center. Please also check ongoing floating volatility patterns of Lipum AB and Freemelt Holding.
Diversification Opportunities for Lipum AB and Freemelt Holding
-0.55 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Lipum and Freemelt is -0.55. Overlapping area represents the amount of risk that can be diversified away by holding Lipum AB and Freemelt Holding AB in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Freemelt Holding and Lipum AB 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 Lipum AB are associated (or correlated) with Freemelt Holding. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Freemelt Holding has no effect on the direction of Lipum AB i.e., Lipum AB and Freemelt Holding go up and down completely randomly.
Pair Corralation between Lipum AB and Freemelt Holding
Assuming the 90 days trading horizon Lipum AB is expected to under-perform the Freemelt Holding. But the stock apears to be less risky and, when comparing its historical volatility, Lipum AB is 2.94 times less risky than Freemelt Holding. The stock trades about -0.01 of its potential returns per unit of risk. The Freemelt Holding AB is currently generating about 0.25 of returns per unit of risk over similar time horizon. If you would invest 101.00 in Freemelt Holding AB on April 24, 2025 and sell it today you would earn a total of 166.00 from holding Freemelt Holding AB or generate 164.36% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Lipum AB vs. Freemelt Holding AB
Performance |
Timeline |
Lipum AB |
Freemelt Holding |
Lipum AB and Freemelt Holding Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Lipum AB and Freemelt Holding
The main advantage of trading using opposite Lipum AB and Freemelt Holding positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Lipum AB position performs unexpectedly, Freemelt Holding 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 Freemelt Holding will offset losses from the drop in Freemelt Holding's long position.Lipum AB vs. Xbrane Biopharma AB | Lipum AB vs. Hansa Biopharma AB | Lipum AB vs. Cantargia AB | Lipum AB vs. Vicore Pharma Holding |
Freemelt Holding vs. BIMobject AB | Freemelt Holding vs. Checkin Group AB | Freemelt Holding vs. Crunchfish AB | Freemelt Holding vs. Midsummer AB |
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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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