Correlation Between Skane Mollan and Kinnevik Investment
Can any of the company-specific risk be diversified away by investing in both Skane Mollan and Kinnevik Investment 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 Skane Mollan and Kinnevik Investment into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Skane mollan AB and Kinnevik Investment AB, you can compare the effects of market volatilities on Skane Mollan and Kinnevik Investment 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 Skane Mollan with a short position of Kinnevik Investment. Check out your portfolio center. Please also check ongoing floating volatility patterns of Skane Mollan and Kinnevik Investment.
Diversification Opportunities for Skane Mollan and Kinnevik Investment
0.09 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Skane and Kinnevik is 0.09. Overlapping area represents the amount of risk that can be diversified away by holding Skane mollan AB and Kinnevik Investment AB in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Kinnevik Investment and Skane Mollan 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 Skane mollan AB are associated (or correlated) with Kinnevik Investment. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Kinnevik Investment has no effect on the direction of Skane Mollan i.e., Skane Mollan and Kinnevik Investment go up and down completely randomly.
Pair Corralation between Skane Mollan and Kinnevik Investment
Assuming the 90 days trading horizon Skane mollan AB is expected to under-perform the Kinnevik Investment. In addition to that, Skane Mollan is 1.33 times more volatile than Kinnevik Investment AB. It trades about -0.02 of its total potential returns per unit of risk. Kinnevik Investment AB is currently generating about 0.04 per unit of volatility. If you would invest 7,508 in Kinnevik Investment AB on September 14, 2024 and sell it today you would earn a total of 333.00 from holding Kinnevik Investment AB or generate 4.44% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Skane mollan AB vs. Kinnevik Investment AB
Performance |
Timeline |
Skane mollan AB |
Kinnevik Investment |
Skane Mollan and Kinnevik Investment Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Skane Mollan and Kinnevik Investment
The main advantage of trading using opposite Skane Mollan and Kinnevik Investment positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Skane Mollan position performs unexpectedly, Kinnevik Investment 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 Kinnevik Investment will offset losses from the drop in Kinnevik Investment's long position.Skane Mollan vs. Rejlers AB | Skane Mollan vs. Stille AB | Skane Mollan vs. New Nordic Healthbrands | Skane Mollan vs. Midsona AB |
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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 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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