Correlation Between LendingTree and Deutsche Pfandbriefbank
Can any of the company-specific risk be diversified away by investing in both LendingTree and Deutsche Pfandbriefbank 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 LendingTree and Deutsche Pfandbriefbank into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between LendingTree and Deutsche Pfandbriefbank AG, you can compare the effects of market volatilities on LendingTree and Deutsche Pfandbriefbank 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 LendingTree with a short position of Deutsche Pfandbriefbank. Check out your portfolio center. Please also check ongoing floating volatility patterns of LendingTree and Deutsche Pfandbriefbank.
Diversification Opportunities for LendingTree and Deutsche Pfandbriefbank
0.71 | Correlation Coefficient |
Poor diversification
The 3 months correlation between LendingTree and Deutsche is 0.71. Overlapping area represents the amount of risk that can be diversified away by holding LendingTree and Deutsche Pfandbriefbank AG in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Deutsche Pfandbriefbank and LendingTree 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 LendingTree are associated (or correlated) with Deutsche Pfandbriefbank. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Deutsche Pfandbriefbank has no effect on the direction of LendingTree i.e., LendingTree and Deutsche Pfandbriefbank go up and down completely randomly.
Pair Corralation between LendingTree and Deutsche Pfandbriefbank
Assuming the 90 days horizon LendingTree is expected to under-perform the Deutsche Pfandbriefbank. In addition to that, LendingTree is 2.22 times more volatile than Deutsche Pfandbriefbank AG. It trades about -0.09 of its total potential returns per unit of risk. Deutsche Pfandbriefbank AG is currently generating about -0.15 per unit of volatility. If you would invest 573.00 in Deutsche Pfandbriefbank AG on September 25, 2024 and sell it today you would lose (100.00) from holding Deutsche Pfandbriefbank AG or give up 17.45% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
LendingTree vs. Deutsche Pfandbriefbank AG
Performance |
Timeline |
LendingTree |
Deutsche Pfandbriefbank |
LendingTree and Deutsche Pfandbriefbank Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with LendingTree and Deutsche Pfandbriefbank
The main advantage of trading using opposite LendingTree and Deutsche Pfandbriefbank positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if LendingTree position performs unexpectedly, Deutsche Pfandbriefbank 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 Deutsche Pfandbriefbank will offset losses from the drop in Deutsche Pfandbriefbank's long position.LendingTree vs. Electronic Arts | LendingTree vs. Gaztransport Technigaz SA | LendingTree vs. LG Electronics | LendingTree vs. Transport International Holdings |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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