Correlation Between DAX Index and Leverage Shares

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Can any of the company-specific risk be diversified away by investing in both DAX Index and Leverage Shares 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 Leverage Shares into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between DAX Index and Leverage Shares 3x, you can compare the effects of market volatilities on DAX Index and Leverage Shares 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 Leverage Shares. Check out your portfolio center. Please also check ongoing floating volatility patterns of DAX Index and Leverage Shares.

Diversification Opportunities for DAX Index and Leverage Shares

0.74
  Correlation Coefficient

Poor diversification

The 3 months correlation between DAX and Leverage is 0.74. Overlapping area represents the amount of risk that can be diversified away by holding DAX Index and Leverage Shares 3x in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Leverage Shares 3x 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 Leverage Shares. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Leverage Shares 3x has no effect on the direction of DAX Index i.e., DAX Index and Leverage Shares go up and down completely randomly.
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Pair Corralation between DAX Index and Leverage Shares

Assuming the 90 days trading horizon DAX Index is expected to generate 0.39 times more return on investment than Leverage Shares. However, DAX Index is 2.59 times less risky than Leverage Shares. It trades about 0.16 of its potential returns per unit of risk. Leverage Shares 3x is currently generating about -0.18 per unit of risk. If you would invest  1,940,520  in DAX Index on September 26, 2024 and sell it today you would earn a total of  44,357  from holding DAX Index or generate 2.29% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthSignificant
Accuracy100.0%
ValuesDaily Returns

DAX Index  vs.  Leverage Shares 3x

 Performance 
       Timeline  

DAX Index and Leverage Shares Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with DAX Index and Leverage Shares

The main advantage of trading using opposite DAX Index and Leverage Shares positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if DAX Index position performs unexpectedly, Leverage Shares 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 Leverage Shares will offset losses from the drop in Leverage Shares' long position.
The idea behind DAX Index and Leverage Shares 3x 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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.

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