Correlation Between Vienna Insurance and VERBUND AG
Can any of the company-specific risk be diversified away by investing in both Vienna Insurance and VERBUND AG 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 VERBUND AG into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Vienna Insurance Group and VERBUND AG, you can compare the effects of market volatilities on Vienna Insurance and VERBUND AG 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 VERBUND AG. Check out your portfolio center. Please also check ongoing floating volatility patterns of Vienna Insurance and VERBUND AG.
Diversification Opportunities for Vienna Insurance and VERBUND AG
0.58 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Vienna and VERBUND is 0.58. Overlapping area represents the amount of risk that can be diversified away by holding Vienna Insurance Group and VERBUND AG in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on VERBUND AG 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 Group are associated (or correlated) with VERBUND AG. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of VERBUND AG has no effect on the direction of Vienna Insurance i.e., Vienna Insurance and VERBUND AG go up and down completely randomly.
Pair Corralation between Vienna Insurance and VERBUND AG
Assuming the 90 days trading horizon Vienna Insurance Group is expected to generate 0.44 times more return on investment than VERBUND AG. However, Vienna Insurance Group is 2.28 times less risky than VERBUND AG. It trades about -0.1 of its potential returns per unit of risk. VERBUND AG is currently generating about -0.07 per unit of risk. If you would invest 2,975 in Vienna Insurance Group on August 27, 2024 and sell it today you would lose (65.00) from holding Vienna Insurance Group or give up 2.18% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Vienna Insurance Group vs. VERBUND AG
Performance |
| Timeline |
| Vienna Insurance |
| VERBUND AG |
Vienna Insurance and VERBUND AG Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Vienna Insurance and VERBUND AG
The main advantage of trading using opposite Vienna Insurance and VERBUND AG positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Vienna Insurance position performs unexpectedly, VERBUND AG 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 VERBUND AG will offset losses from the drop in VERBUND AG's long position.| Vienna Insurance vs. Erste Group Bank | Vienna Insurance vs. UNIQA Insurance Group | Vienna Insurance vs. Raiffeisen Bank International | Vienna Insurance vs. Voestalpine AG |
| VERBUND AG vs. OMV Aktiengesellschaft | VERBUND AG vs. Voestalpine AG | VERBUND AG vs. Wienerberger AG | VERBUND AG vs. EVN AG |
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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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