Correlation Between Volkswagen and Automatic Data
Can any of the company-specific risk be diversified away by investing in both Volkswagen and Automatic 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 Volkswagen and Automatic Data into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Volkswagen AG and Automatic Data Processing, you can compare the effects of market volatilities on Volkswagen and Automatic 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 Volkswagen with a short position of Automatic Data. Check out your portfolio center. Please also check ongoing floating volatility patterns of Volkswagen and Automatic Data.
Diversification Opportunities for Volkswagen and Automatic Data
-0.87 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Volkswagen and Automatic is -0.87. Overlapping area represents the amount of risk that can be diversified away by holding Volkswagen AG and Automatic Data Processing in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Automatic Data Processing and Volkswagen 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 Volkswagen AG are associated (or correlated) with Automatic Data. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Automatic Data Processing has no effect on the direction of Volkswagen i.e., Volkswagen and Automatic Data go up and down completely randomly.
Pair Corralation between Volkswagen and Automatic Data
Assuming the 90 days trading horizon Volkswagen AG is expected to generate 1.73 times more return on investment than Automatic Data. However, Volkswagen is 1.73 times more volatile than Automatic Data Processing. It trades about 0.16 of its potential returns per unit of risk. Automatic Data Processing is currently generating about -0.1 per unit of risk. If you would invest 8,708 in Volkswagen AG on October 10, 2024 and sell it today you would earn a total of 397.00 from holding Volkswagen AG or generate 4.56% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Significant |
| Accuracy | 95.24% |
| Values | Daily Returns |
Volkswagen AG vs. Automatic Data Processing
Performance |
| Timeline |
| Volkswagen AG |
| Automatic Data Processing |
Volkswagen and Automatic Data Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Volkswagen and Automatic Data
The main advantage of trading using opposite Volkswagen and Automatic Data positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Volkswagen position performs unexpectedly, Automatic 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 Automatic Data will offset losses from the drop in Automatic Data's long position.| Volkswagen vs. EJF Investments | Volkswagen vs. Compagnie Plastic Omnium | Volkswagen vs. BlackRock Frontiers Investment | Volkswagen vs. Cembra Money Bank |
| Automatic Data vs. Dalata Hotel Group | Automatic Data vs. Coeur Mining | Automatic Data vs. Caledonia Investments | Automatic Data vs. First Class Metals |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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