Correlation Between Clean Seas and SpareBank
Can any of the company-specific risk be diversified away by investing in both Clean Seas and 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 Clean Seas and SpareBank into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Clean Seas Seafood and SpareBank 1 stlandet, you can compare the effects of market volatilities on Clean Seas and 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 Clean Seas with a short position of SpareBank. Check out your portfolio center. Please also check ongoing floating volatility patterns of Clean Seas and SpareBank.
Diversification Opportunities for Clean Seas and SpareBank
-0.57 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Clean and SpareBank is -0.57. Overlapping area represents the amount of risk that can be diversified away by holding Clean Seas Seafood and SpareBank 1 stlandet in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SpareBank 1 stlandet and Clean Seas 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 Clean Seas Seafood are associated (or correlated) with SpareBank. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SpareBank 1 stlandet has no effect on the direction of Clean Seas i.e., Clean Seas and SpareBank go up and down completely randomly.
Pair Corralation between Clean Seas and SpareBank
Assuming the 90 days trading horizon Clean Seas Seafood is expected to under-perform the SpareBank. In addition to that, Clean Seas is 3.09 times more volatile than SpareBank 1 stlandet. It trades about -0.17 of its total potential returns per unit of risk. SpareBank 1 stlandet is currently generating about 0.07 per unit of volatility. If you would invest 13,572 in SpareBank 1 stlandet on September 1, 2024 and sell it today you would earn a total of 1,502 from holding SpareBank 1 stlandet or generate 11.07% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Clean Seas Seafood vs. SpareBank 1 stlandet
Performance |
| Timeline |
| Clean Seas Seafood |
| SpareBank 1 stlandet |
Clean Seas and SpareBank Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Clean Seas and SpareBank
The main advantage of trading using opposite Clean Seas and SpareBank positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Clean Seas position performs unexpectedly, 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 SpareBank will offset losses from the drop in SpareBank's long position.| Clean Seas vs. Masoval AS | Clean Seas vs. Andfjord Salmon AS | Clean Seas vs. Arctic Fish Holding | Clean Seas vs. Ice Fish Farm |
| SpareBank vs. Sparebank 1 SMN | SpareBank vs. Sparebank 1 Nord Norge | SpareBank vs. Sparebanken Vest | SpareBank vs. Sparebank 1 SR |
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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