Correlation Between DAX Index and Verisk Analytics

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Can any of the company-specific risk be diversified away by investing in both DAX Index and Verisk Analytics 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 Verisk Analytics into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between DAX Index and Verisk Analytics, you can compare the effects of market volatilities on DAX Index and Verisk Analytics 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 Verisk Analytics. Check out your portfolio center. Please also check ongoing floating volatility patterns of DAX Index and Verisk Analytics.

Diversification Opportunities for DAX Index and Verisk Analytics

0.39
  Correlation Coefficient

Weak diversification

The 3 months correlation between DAX and Verisk is 0.39. Overlapping area represents the amount of risk that can be diversified away by holding DAX Index and Verisk Analytics in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Verisk Analytics 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 Verisk Analytics. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Verisk Analytics has no effect on the direction of DAX Index i.e., DAX Index and Verisk Analytics go up and down completely randomly.
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Pair Corralation between DAX Index and Verisk Analytics

Assuming the 90 days trading horizon DAX Index is expected to generate 0.87 times more return on investment than Verisk Analytics. However, DAX Index is 1.15 times less risky than Verisk Analytics. It trades about 0.17 of its potential returns per unit of risk. Verisk Analytics is currently generating about 0.05 per unit of risk. If you would invest  1,990,914  in DAX Index on December 30, 2024 and sell it today you would earn a total of  255,238  from holding DAX Index or generate 12.82% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthVery Weak
Accuracy100.0%
ValuesDaily Returns

DAX Index  vs.  Verisk Analytics

 Performance 
       Timeline  

DAX Index and Verisk Analytics Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with DAX Index and Verisk Analytics

The main advantage of trading using opposite DAX Index and Verisk Analytics positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if DAX Index position performs unexpectedly, Verisk Analytics 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 Verisk Analytics will offset losses from the drop in Verisk Analytics' long position.
The idea behind DAX Index and Verisk Analytics 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 Analyst Advice module to analyst recommendations and target price estimates broken down by several categories.

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