Correlation Between BankInvest Optima and Agillic AS
Can any of the company-specific risk be diversified away by investing in both BankInvest Optima and Agillic AS 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 BankInvest Optima and Agillic AS into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between BankInvest Optima 30 and Agillic AS, you can compare the effects of market volatilities on BankInvest Optima and Agillic AS 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 BankInvest Optima with a short position of Agillic AS. Check out your portfolio center. Please also check ongoing floating volatility patterns of BankInvest Optima and Agillic AS.
Diversification Opportunities for BankInvest Optima and Agillic AS
-0.79 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between BankInvest and Agillic is -0.79. Overlapping area represents the amount of risk that can be diversified away by holding BankInvest Optima 30 and Agillic AS in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Agillic AS and BankInvest Optima 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 BankInvest Optima 30 are associated (or correlated) with Agillic AS. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Agillic AS has no effect on the direction of BankInvest Optima i.e., BankInvest Optima and Agillic AS go up and down completely randomly.
Pair Corralation between BankInvest Optima and Agillic AS
Assuming the 90 days trading horizon BankInvest Optima 30 is expected to generate 0.16 times more return on investment than Agillic AS. However, BankInvest Optima 30 is 6.08 times less risky than Agillic AS. It trades about 0.1 of its potential returns per unit of risk. Agillic AS is currently generating about -0.07 per unit of risk. If you would invest 9,362 in BankInvest Optima 30 on September 13, 2024 and sell it today you would earn a total of 1,873 from holding BankInvest Optima 30 or generate 20.01% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 97.58% |
| Values | Daily Returns |
BankInvest Optima 30 vs. Agillic AS
Performance |
| Timeline |
| BankInvest Optima |
| Agillic AS |
BankInvest Optima and Agillic AS Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with BankInvest Optima and Agillic AS
The main advantage of trading using opposite BankInvest Optima and Agillic AS positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if BankInvest Optima position performs unexpectedly, Agillic AS 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 Agillic AS will offset losses from the drop in Agillic AS's long position.| BankInvest Optima vs. Novo Nordisk AS | BankInvest Optima vs. Nordea Bank Abp | BankInvest Optima vs. DSV Panalpina AS | BankInvest Optima vs. AP Mller |
| Agillic AS vs. cBrain AS | Agillic AS vs. Danske Invest | Agillic AS vs. BankInvest Optima 30 | Agillic AS vs. Gabriel Holding |
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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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