Correlation Between INTER CARS and Regions Financial
Can any of the company-specific risk be diversified away by investing in both INTER CARS and Regions Financial 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 INTER CARS and Regions Financial into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between INTER CARS SA and Regions Financial, you can compare the effects of market volatilities on INTER CARS and Regions Financial 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 INTER CARS with a short position of Regions Financial. Check out your portfolio center. Please also check ongoing floating volatility patterns of INTER CARS and Regions Financial.
Diversification Opportunities for INTER CARS and Regions Financial
0.29 | Correlation Coefficient |
Modest diversification
The 3 months correlation between INTER and Regions is 0.29. Overlapping area represents the amount of risk that can be diversified away by holding INTER CARS SA and Regions Financial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Regions Financial and INTER CARS 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 INTER CARS SA are associated (or correlated) with Regions Financial. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Regions Financial has no effect on the direction of INTER CARS i.e., INTER CARS and Regions Financial go up and down completely randomly.
Pair Corralation between INTER CARS and Regions Financial
Assuming the 90 days horizon INTER CARS SA is expected to generate 1.34 times more return on investment than Regions Financial. However, INTER CARS is 1.34 times more volatile than Regions Financial. It trades about 0.04 of its potential returns per unit of risk. Regions Financial is currently generating about -0.1 per unit of risk. If you would invest 11,980 in INTER CARS SA on December 30, 2024 and sell it today you would earn a total of 440.00 from holding INTER CARS SA or generate 3.67% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
INTER CARS SA vs. Regions Financial
Performance |
Timeline |
INTER CARS SA |
Regions Financial |
INTER CARS and Regions Financial Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with INTER CARS and Regions Financial
The main advantage of trading using opposite INTER CARS and Regions Financial positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if INTER CARS position performs unexpectedly, Regions Financial 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 Regions Financial will offset losses from the drop in Regions Financial's long position.INTER CARS vs. Khiron Life Sciences | INTER CARS vs. COSMOSTEEL HLDGS | INTER CARS vs. MOUNT GIBSON IRON | INTER CARS vs. Nippon Steel |
Regions Financial vs. Magnachip Semiconductor | Regions Financial vs. Semiconductor Manufacturing International | Regions Financial vs. CVS Health | Regions Financial vs. OPKO HEALTH |
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 Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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