Correlation Between Auto Trader and United States
Can any of the company-specific risk be diversified away by investing in both Auto Trader and United States 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 Auto Trader and United States into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Auto Trader Group and United States Steel, you can compare the effects of market volatilities on Auto Trader and United States 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 Auto Trader with a short position of United States. Check out your portfolio center. Please also check ongoing floating volatility patterns of Auto Trader and United States.
Diversification Opportunities for Auto Trader and United States
0.39 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Auto and United is 0.39. Overlapping area represents the amount of risk that can be diversified away by holding Auto Trader Group and United States Steel in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on United States Steel and Auto Trader 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 Auto Trader Group are associated (or correlated) with United States. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of United States Steel has no effect on the direction of Auto Trader i.e., Auto Trader and United States go up and down completely randomly.
Pair Corralation between Auto Trader and United States
Assuming the 90 days trading horizon Auto Trader Group is expected to under-perform the United States. But the stock apears to be less risky and, when comparing its historical volatility, Auto Trader Group is 2.14 times less risky than United States. The stock trades about -0.01 of its potential returns per unit of risk. The United States Steel is currently generating about 0.41 of returns per unit of risk over similar time horizon. If you would invest 3,071 in United States Steel on November 4, 2024 and sell it today you would earn a total of 681.00 from holding United States Steel or generate 22.18% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Auto Trader Group vs. United States Steel
Performance |
| Timeline |
| Auto Trader Group |
| United States Steel |
Auto Trader and United States Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Auto Trader and United States
The main advantage of trading using opposite Auto Trader and United States positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Auto Trader position performs unexpectedly, United States 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 United States will offset losses from the drop in United States' long position.| Auto Trader vs. Vienna Insurance Group | Auto Trader vs. Lowland Investment Co | Auto Trader vs. Vietnam Enterprise Investments | Auto Trader vs. EJF Investments |
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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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