Correlation Between MARKET VECTR and DAX Index

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

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

Diversification Opportunities for MARKET VECTR and DAX Index

0.8

Correlation Coefficient

MARKET VECTR  DAX Index

Very poor diversification

The 3 months correlation between MARKET and DAX is 0.8. Overlapping area represents the amount of risk that can be diversified away by holding MARKET VECTR RETAIL and DAX Index in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on DAX Index and MARKET VECTR 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 MARKET VECTR RETAIL are associated (or correlated) with DAX Index. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of DAX Index has no effect on the direction of MARKET VECTR i.e., MARKET VECTR and DAX Index go up and down completely randomly.

Pair Corralation between MARKET VECTR and DAX Index

Assuming the 90 days trading horizon MARKET VECTR is expected to generate 11.61 times less return on investment than DAX Index. But when comparing it to its historical volatility, MARKET VECTR RETAIL is 1.09 times less risky than DAX Index. It trades about 0.03 of its potential returns per unit of risk. DAX Index is currently generating about 0.34 of returns per unit of risk over similar time horizon. If you would invest  1,926,175  in DAX Index on November 27, 2024 and sell it today you would earn a total of  314,852  from holding DAX Index or generate 16.35% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Strong
Accuracy	98.33%
Values	Daily Returns

MARKET VECTR RETAIL  vs.  DAX Index

Pair Trading with MARKET VECTR and DAX Index

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

The idea behind MARKET VECTR RETAIL and DAX Index 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.

Check out your portfolio center.

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.