Correlation Between DAX Index and Ecora Resources

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

Diversification Opportunities for DAX Index and Ecora Resources

-0.07
  Correlation Coefficient

Good diversification

The 3 months correlation between DAX and Ecora is -0.07. Overlapping area represents the amount of risk that can be diversified away by holding DAX Index and Ecora Resources PLC in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ecora Resources PLC 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 Ecora Resources. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ecora Resources PLC has no effect on the direction of DAX Index i.e., DAX Index and Ecora Resources go up and down completely randomly.
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Pair Corralation between DAX Index and Ecora Resources

Assuming the 90 days trading horizon DAX Index is expected to generate 0.38 times more return on investment than Ecora Resources. However, DAX Index is 2.66 times less risky than Ecora Resources. It trades about 0.08 of its potential returns per unit of risk. Ecora Resources PLC is currently generating about 0.0 per unit of risk. If you would invest  1,937,762  in DAX Index on September 23, 2024 and sell it today you would earn a total of  50,713  from holding DAX Index or generate 2.62% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Against 
StrengthInsignificant
Accuracy100.0%
ValuesDaily Returns

DAX Index  vs.  Ecora Resources PLC

 Performance 
       Timeline  

DAX Index and Ecora Resources Volatility Contrast

   Predicted Return Density   
       Returns  

Pair Trading with DAX Index and Ecora Resources

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