Correlation Between Volkswagen and Perusahaan Perseroan
Can any of the company-specific risk be diversified away by investing in both Volkswagen and Perusahaan Perseroan 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 Perusahaan Perseroan into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Volkswagen AG and Perusahaan Perseroan PT, you can compare the effects of market volatilities on Volkswagen and Perusahaan Perseroan 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 Perusahaan Perseroan. Check out your portfolio center. Please also check ongoing floating volatility patterns of Volkswagen and Perusahaan Perseroan.
Diversification Opportunities for Volkswagen and Perusahaan Perseroan
0.74 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Volkswagen and Perusahaan is 0.74. Overlapping area represents the amount of risk that can be diversified away by holding Volkswagen AG and Perusahaan Perseroan PT in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Perusahaan Perseroan 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 Perusahaan Perseroan. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Perusahaan Perseroan has no effect on the direction of Volkswagen i.e., Volkswagen and Perusahaan Perseroan go up and down completely randomly.
Pair Corralation between Volkswagen and Perusahaan Perseroan
Assuming the 90 days horizon Volkswagen AG is expected to under-perform the Perusahaan Perseroan. But the stock apears to be less risky and, when comparing its historical volatility, Volkswagen AG is 2.13 times less risky than Perusahaan Perseroan. The stock trades about -0.22 of its potential returns per unit of risk. The Perusahaan Perseroan PT is currently generating about -0.04 of returns per unit of risk over similar time horizon. If you would invest 1,670 in Perusahaan Perseroan PT on August 30, 2024 and sell it today you would lose (100.00) from holding Perusahaan Perseroan PT or give up 5.99% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Volkswagen AG vs. Perusahaan Perseroan PT
Performance |
| Timeline |
| Volkswagen AG |
| Perusahaan Perseroan |
Volkswagen and Perusahaan Perseroan Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Volkswagen and Perusahaan Perseroan
The main advantage of trading using opposite Volkswagen and Perusahaan Perseroan positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Volkswagen position performs unexpectedly, Perusahaan Perseroan 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 Perusahaan Perseroan will offset losses from the drop in Perusahaan Perseroan's long position.| Volkswagen vs. Tesla Inc | Volkswagen vs. Toyota Motor | Volkswagen vs. Toyota Motor | Volkswagen vs. BYD Company Limited |
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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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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