Correlation Between Gjensidige Forsikring and Olav Thon
Can any of the company-specific risk be diversified away by investing in both Gjensidige Forsikring and Olav Thon 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 Gjensidige Forsikring and Olav Thon into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Gjensidige Forsikring ASA and Olav Thon Eien, you can compare the effects of market volatilities on Gjensidige Forsikring and Olav Thon 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 Gjensidige Forsikring with a short position of Olav Thon. Check out your portfolio center. Please also check ongoing floating volatility patterns of Gjensidige Forsikring and Olav Thon.
Diversification Opportunities for Gjensidige Forsikring and Olav Thon
-0.3 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Gjensidige and Olav is -0.3. Overlapping area represents the amount of risk that can be diversified away by holding Gjensidige Forsikring ASA and Olav Thon Eien in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Olav Thon Eien and Gjensidige Forsikring 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 Gjensidige Forsikring ASA are associated (or correlated) with Olav Thon. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Olav Thon Eien has no effect on the direction of Gjensidige Forsikring i.e., Gjensidige Forsikring and Olav Thon go up and down completely randomly.
Pair Corralation between Gjensidige Forsikring and Olav Thon
Assuming the 90 days trading horizon Gjensidige Forsikring ASA is expected to generate 1.36 times more return on investment than Olav Thon. However, Gjensidige Forsikring is 1.36 times more volatile than Olav Thon Eien. It trades about 0.12 of its potential returns per unit of risk. Olav Thon Eien is currently generating about -0.06 per unit of risk. If you would invest 18,600 in Gjensidige Forsikring ASA on September 4, 2024 and sell it today you would earn a total of 1,520 from holding Gjensidige Forsikring ASA or generate 8.17% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Gjensidige Forsikring ASA vs. Olav Thon Eien
Performance |
Timeline |
Gjensidige Forsikring ASA |
Olav Thon Eien |
Gjensidige Forsikring and Olav Thon Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Gjensidige Forsikring and Olav Thon
The main advantage of trading using opposite Gjensidige Forsikring and Olav Thon positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Gjensidige Forsikring position performs unexpectedly, Olav Thon 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 Olav Thon will offset losses from the drop in Olav Thon's long position.Gjensidige Forsikring vs. DnB ASA | Gjensidige Forsikring vs. Storebrand ASA | Gjensidige Forsikring vs. Orkla ASA | Gjensidige Forsikring vs. Telenor ASA |
Olav Thon vs. Entra ASA | Olav Thon vs. Veidekke ASA | Olav Thon vs. Selvaag Bolig ASA | Olav Thon vs. Storebrand ASA |
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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