Correlation Between DAX Index and UNIQA INSURANCE

Can any of the company-specific risk be diversified away by investing in both DAX Index and UNIQA INSURANCE 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 DAX Index and UNIQA INSURANCE into the same portfolio, which is an essential part of the fundamental portfolio management process.

By analyzing existing cross correlation between DAX Index and UNIQA INSURANCE GR, you can compare the effects of market volatilities on DAX Index and UNIQA INSURANCE 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 DAX Index with a short position of UNIQA INSURANCE. Check out your portfolio center. Please also check ongoing floating volatility patterns of DAX Index and UNIQA INSURANCE.

Diversification Opportunities for DAX Index and UNIQA INSURANCE

0.22

Correlation Coefficient

DAX Index  UNIQA INSURANCE

Modest diversification

The 3 months correlation between DAX and UNIQA is 0.22. Overlapping area represents the amount of risk that can be diversified away by holding DAX Index and UNIQA INSURANCE GR in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on UNIQA INSURANCE GR and DAX Index 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 DAX Index are associated (or correlated) with UNIQA INSURANCE. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of UNIQA INSURANCE GR has no effect on the direction of DAX Index i.e., DAX Index and UNIQA INSURANCE go up and down completely randomly.

Pair Corralation between DAX Index and UNIQA INSURANCE

Assuming the 90 days trading horizon DAX Index is expected to generate 0.72 times more return on investment than UNIQA INSURANCE. However, DAX Index is 1.38 times less risky than UNIQA INSURANCE. It trades about 0.11 of its potential returns per unit of risk. UNIQA INSURANCE GR is currently generating about 0.04 per unit of risk. If you would invest  1,884,679  in DAX Index on September 23, 2024 and sell it today you would earn a total of  103,796  from holding DAX Index or generate 5.51% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Very Weak
Accuracy	100.0%
Values	Daily Returns

DAX Index  vs.  UNIQA INSURANCE GR

Pair Trading with DAX Index and UNIQA INSURANCE

The main advantage of trading using opposite DAX Index and UNIQA INSURANCE positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if DAX Index position performs unexpectedly, UNIQA INSURANCE 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 UNIQA INSURANCE will offset losses from the drop in UNIQA INSURANCE's long position.

The idea behind DAX Index and UNIQA INSURANCE GR pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.

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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.