Correlation Between Kongsberg Gruppen and Telenor ASA
Can any of the company-specific risk be diversified away by investing in both Kongsberg Gruppen and Telenor ASA 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 Kongsberg Gruppen and Telenor ASA into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Kongsberg Gruppen ASA and Telenor ASA, you can compare the effects of market volatilities on Kongsberg Gruppen and Telenor ASA 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 Kongsberg Gruppen with a short position of Telenor ASA. Check out your portfolio center. Please also check ongoing floating volatility patterns of Kongsberg Gruppen and Telenor ASA.
Diversification Opportunities for Kongsberg Gruppen and Telenor ASA
-0.19 | Correlation Coefficient |
Good diversification
The 3 months correlation between Kongsberg and Telenor is -0.19. Overlapping area represents the amount of risk that can be diversified away by holding Kongsberg Gruppen ASA and Telenor ASA in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Telenor ASA and Kongsberg Gruppen 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 Kongsberg Gruppen ASA are associated (or correlated) with Telenor ASA. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Telenor ASA has no effect on the direction of Kongsberg Gruppen i.e., Kongsberg Gruppen and Telenor ASA go up and down completely randomly.
Pair Corralation between Kongsberg Gruppen and Telenor ASA
Assuming the 90 days trading horizon Kongsberg Gruppen is expected to generate 1.13 times less return on investment than Telenor ASA. In addition to that, Kongsberg Gruppen is 1.78 times more volatile than Telenor ASA. It trades about 0.16 of its total potential returns per unit of risk. Telenor ASA is currently generating about 0.33 per unit of volatility. If you would invest 12,950 in Telenor ASA on November 2, 2024 and sell it today you would earn a total of 930.00 from holding Telenor ASA or generate 7.18% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Kongsberg Gruppen ASA vs. Telenor ASA
Performance |
| Timeline |
| Kongsberg Gruppen ASA |
| Telenor ASA |
Kongsberg Gruppen and Telenor ASA Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Kongsberg Gruppen and Telenor ASA
The main advantage of trading using opposite Kongsberg Gruppen and Telenor ASA positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Kongsberg Gruppen position performs unexpectedly, Telenor ASA 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 Telenor ASA will offset losses from the drop in Telenor ASA's long position.| Kongsberg Gruppen vs. DnB ASA | Kongsberg Gruppen vs. Orkla ASA | Kongsberg Gruppen vs. Storebrand ASA | Kongsberg Gruppen vs. Yara International ASA |
| Telenor ASA vs. Orkla ASA | Telenor ASA vs. DnB ASA | Telenor ASA vs. Yara International ASA | Telenor ASA 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 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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