Correlation Between CVB Financial and Daimler Truck
Can any of the company-specific risk be diversified away by investing in both CVB Financial and Daimler Truck 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 CVB Financial and Daimler Truck into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between CVB Financial Corp and Daimler Truck Holding, you can compare the effects of market volatilities on CVB Financial and Daimler Truck 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 CVB Financial with a short position of Daimler Truck. Check out your portfolio center. Please also check ongoing floating volatility patterns of CVB Financial and Daimler Truck.
Diversification Opportunities for CVB Financial and Daimler Truck
-0.13 | Correlation Coefficient |
Good diversification
The 3 months correlation between CVB and Daimler is -0.13. Overlapping area represents the amount of risk that can be diversified away by holding CVB Financial Corp and Daimler Truck Holding in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Daimler Truck Holding and CVB Financial 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 CVB Financial Corp are associated (or correlated) with Daimler Truck. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Daimler Truck Holding has no effect on the direction of CVB Financial i.e., CVB Financial and Daimler Truck go up and down completely randomly.
Pair Corralation between CVB Financial and Daimler Truck
Assuming the 90 days horizon CVB Financial Corp is expected to under-perform the Daimler Truck. But the stock apears to be less risky and, when comparing its historical volatility, CVB Financial Corp is 1.71 times less risky than Daimler Truck. The stock trades about -0.21 of its potential returns per unit of risk. The Daimler Truck Holding is currently generating about 0.04 of returns per unit of risk over similar time horizon. If you would invest 3,658 in Daimler Truck Holding on December 22, 2024 and sell it today you would earn a total of 188.00 from holding Daimler Truck Holding or generate 5.14% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
CVB Financial Corp vs. Daimler Truck Holding
Performance |
Timeline |
CVB Financial Corp |
Daimler Truck Holding |
CVB Financial and Daimler Truck Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with CVB Financial and Daimler Truck
The main advantage of trading using opposite CVB Financial and Daimler Truck positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if CVB Financial position performs unexpectedly, Daimler Truck 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 Daimler Truck will offset losses from the drop in Daimler Truck's long position.CVB Financial vs. T MOBILE US | CVB Financial vs. Kaufman Broad SA | CVB Financial vs. Gaztransport Technigaz SA | CVB Financial vs. SBA Communications Corp |
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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 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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