Correlation Between VIENNA INSURANCE and Mühlbauer Holding
Can any of the company-specific risk be diversified away by investing in both VIENNA INSURANCE and Mühlbauer Holding 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 VIENNA INSURANCE and Mühlbauer Holding into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between VIENNA INSURANCE GR and Mhlbauer Holding AG, you can compare the effects of market volatilities on VIENNA INSURANCE and Mühlbauer Holding 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 VIENNA INSURANCE with a short position of Mühlbauer Holding. Check out your portfolio center. Please also check ongoing floating volatility patterns of VIENNA INSURANCE and Mühlbauer Holding.
Diversification Opportunities for VIENNA INSURANCE and Mühlbauer Holding
0.64 | Correlation Coefficient |
Poor diversification
The 3 months correlation between VIENNA and Mühlbauer is 0.64. Overlapping area represents the amount of risk that can be diversified away by holding VIENNA INSURANCE GR and Mhlbauer Holding AG in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Mühlbauer Holding and VIENNA INSURANCE 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 VIENNA INSURANCE GR are associated (or correlated) with Mühlbauer Holding. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Mühlbauer Holding has no effect on the direction of VIENNA INSURANCE i.e., VIENNA INSURANCE and Mühlbauer Holding go up and down completely randomly.
Pair Corralation between VIENNA INSURANCE and Mühlbauer Holding
Assuming the 90 days trading horizon VIENNA INSURANCE GR is expected to generate 0.81 times more return on investment than Mühlbauer Holding. However, VIENNA INSURANCE GR is 1.24 times less risky than Mühlbauer Holding. It trades about 0.38 of its potential returns per unit of risk. Mhlbauer Holding AG is currently generating about 0.09 per unit of risk. If you would invest 3,025 in VIENNA INSURANCE GR on December 24, 2024 and sell it today you would earn a total of 920.00 from holding VIENNA INSURANCE GR or generate 30.41% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 98.36% |
Values | Daily Returns |
VIENNA INSURANCE GR vs. Mhlbauer Holding AG
Performance |
Timeline |
VIENNA INSURANCE |
Mühlbauer Holding |
VIENNA INSURANCE and Mühlbauer Holding Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with VIENNA INSURANCE and Mühlbauer Holding
The main advantage of trading using opposite VIENNA INSURANCE and Mühlbauer Holding positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if VIENNA INSURANCE position performs unexpectedly, Mühlbauer Holding 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 Mühlbauer Holding will offset losses from the drop in Mühlbauer Holding's long position.VIENNA INSURANCE vs. EBRO FOODS | VIENNA INSURANCE vs. Monster Beverage Corp | VIENNA INSURANCE vs. Nomad Foods | VIENNA INSURANCE vs. SENECA FOODS A |
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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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