Correlation Between Grong Sparebank and Skue Sparebank
Can any of the company-specific risk be diversified away by investing in both Grong Sparebank and Skue Sparebank 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 Grong Sparebank and Skue Sparebank into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Grong Sparebank and Skue Sparebank, you can compare the effects of market volatilities on Grong Sparebank and Skue Sparebank 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 Grong Sparebank with a short position of Skue Sparebank. Check out your portfolio center. Please also check ongoing floating volatility patterns of Grong Sparebank and Skue Sparebank.
Diversification Opportunities for Grong Sparebank and Skue Sparebank
0.4 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Grong and Skue is 0.4. Overlapping area represents the amount of risk that can be diversified away by holding Grong Sparebank and Skue Sparebank in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Skue Sparebank and Grong Sparebank 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 Grong Sparebank are associated (or correlated) with Skue Sparebank. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Skue Sparebank has no effect on the direction of Grong Sparebank i.e., Grong Sparebank and Skue Sparebank go up and down completely randomly.
Pair Corralation between Grong Sparebank and Skue Sparebank
Assuming the 90 days trading horizon Grong Sparebank is expected to generate 2.88 times less return on investment than Skue Sparebank. But when comparing it to its historical volatility, Grong Sparebank is 1.15 times less risky than Skue Sparebank. It trades about 0.02 of its potential returns per unit of risk. Skue Sparebank is currently generating about 0.06 of returns per unit of risk over similar time horizon. If you would invest 24,795 in Skue Sparebank on September 3, 2024 and sell it today you would earn a total of 1,105 from holding Skue Sparebank or generate 4.46% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Grong Sparebank vs. Skue Sparebank
Performance |
Timeline |
Grong Sparebank |
Skue Sparebank |
Grong Sparebank and Skue Sparebank Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Grong Sparebank and Skue Sparebank
The main advantage of trading using opposite Grong Sparebank and Skue Sparebank positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Grong Sparebank position performs unexpectedly, Skue Sparebank 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 Skue Sparebank will offset losses from the drop in Skue Sparebank's long position.Grong Sparebank vs. Techstep ASA | Grong Sparebank vs. Grieg Seafood ASA | Grong Sparebank vs. Odfjell Drilling | Grong Sparebank vs. Arcticzymes Technologies ASA |
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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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