Correlation Between DAX Index and Carnegie Clean

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

By analyzing existing cross correlation between DAX Index and Carnegie Clean Energy, you can compare the effects of market volatilities on DAX Index and Carnegie Clean 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 Carnegie Clean. Check out your portfolio center. Please also check ongoing floating volatility patterns of DAX Index and Carnegie Clean.

Diversification Opportunities for DAX Index and Carnegie Clean

0.04

Correlation Coefficient

DAX Index  Carnegie Clean

Significant diversification

The 3 months correlation between DAX and Carnegie is 0.04. Overlapping area represents the amount of risk that can be diversified away by holding DAX Index and Carnegie Clean Energy in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Carnegie Clean Energy 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 Carnegie Clean. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Carnegie Clean Energy has no effect on the direction of DAX Index i.e., DAX Index and Carnegie Clean go up and down completely randomly.

Pair Corralation between DAX Index and Carnegie Clean

Assuming the 90 days trading horizon DAX Index is expected to generate 1.48 times less return on investment than Carnegie Clean. But when comparing it to its historical volatility, DAX Index is 9.45 times less risky than Carnegie Clean. It trades about 0.08 of its potential returns per unit of risk. Carnegie Clean Energy is currently generating about 0.01 of returns per unit of risk over similar time horizon. If you would invest  5.00  in Carnegie Clean Energy on October 9, 2024 and sell it today you would lose (2.96) from holding Carnegie Clean Energy or give up 59.2% of portfolio value over 90 days.

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

DAX Index  vs.  Carnegie Clean Energy

Pair Trading with DAX Index and Carnegie Clean

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

The idea behind DAX Index and Carnegie Clean Energy 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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.