Correlation Between Fidelity National and Northern Data
Can any of the company-specific risk be diversified away by investing in both Fidelity National and Northern Data 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 Fidelity National and Northern Data into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Fidelity National Information and Northern Data AG, you can compare the effects of market volatilities on Fidelity National and Northern Data 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 Fidelity National with a short position of Northern Data. Check out your portfolio center. Please also check ongoing floating volatility patterns of Fidelity National and Northern Data.
Diversification Opportunities for Fidelity National and Northern Data
0.62 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Fidelity and Northern is 0.62. Overlapping area represents the amount of risk that can be diversified away by holding Fidelity National Information and Northern Data AG in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Northern Data AG and Fidelity National 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 Fidelity National Information are associated (or correlated) with Northern Data. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Northern Data AG has no effect on the direction of Fidelity National i.e., Fidelity National and Northern Data go up and down completely randomly.
Pair Corralation between Fidelity National and Northern Data
Assuming the 90 days trading horizon Fidelity National Information is expected to generate 0.77 times more return on investment than Northern Data. However, Fidelity National Information is 1.3 times less risky than Northern Data. It trades about -0.06 of its potential returns per unit of risk. Northern Data AG is currently generating about -0.22 per unit of risk. If you would invest 7,785 in Fidelity National Information on December 26, 2024 and sell it today you would lose (945.00) from holding Fidelity National Information or give up 12.14% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Fidelity National Information vs. Northern Data AG
Performance |
Timeline |
Fidelity National |
Northern Data AG |
Fidelity National and Northern Data Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Fidelity National and Northern Data
The main advantage of trading using opposite Fidelity National and Northern Data positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Fidelity National position performs unexpectedly, Northern Data 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 Northern Data will offset losses from the drop in Northern Data's long position.Fidelity National vs. Mitsui Chemicals | Fidelity National vs. AIR PRODCHEMICALS | Fidelity National vs. Sunny Optical Technology | Fidelity National vs. NISSAN CHEMICAL IND |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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