Correlation Between Ford and Agillic AS
Can any of the company-specific risk be diversified away by investing in both Ford 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 Ford and Agillic AS into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ford Motor and Agillic AS, you can compare the effects of market volatilities on Ford 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 Ford with a short position of Agillic AS. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ford and Agillic AS.
Diversification Opportunities for Ford and Agillic AS
-0.73 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Ford and Agillic is -0.73. Overlapping area represents the amount of risk that can be diversified away by holding Ford Motor and Agillic AS in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Agillic AS and Ford 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 Ford Motor 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 Ford i.e., Ford and Agillic AS go up and down completely randomly.
Pair Corralation between Ford and Agillic AS
Taking into account the 90-day investment horizon Ford Motor is expected to under-perform the Agillic AS. In addition to that, Ford is 1.22 times more volatile than Agillic AS. It trades about -0.03 of its total potential returns per unit of risk. Agillic AS is currently generating about -0.03 per unit of volatility. If you would invest 1,290 in Agillic AS on January 19, 2024 and sell it today you would lose (20.00) from holding Agillic AS or give up 1.55% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 90.91% |
| Values | Daily Returns |
Ford Motor vs. Agillic AS
Performance |
| Timeline |
| Ford Motor |
| Agillic AS |
Ford and Agillic AS Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Ford and Agillic AS
The main advantage of trading using opposite Ford and Agillic AS positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ford 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.The idea behind Ford Motor and Agillic AS pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.| Agillic AS vs. Danske Andelskassers Bank | Agillic AS vs. Groenlandsbanken AS | Agillic AS vs. Ringkjoebing Landbobank AS | Agillic AS vs. PARKEN Sport Entertainment |
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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