Correlation Between PLAYTIKA HOLDING and DAX Index

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

By analyzing existing cross correlation between PLAYTIKA HOLDING DL 01 and DAX Index, you can compare the effects of market volatilities on PLAYTIKA HOLDING 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 PLAYTIKA HOLDING with a short position of DAX Index. Check out your portfolio center. Please also check ongoing floating volatility patterns of PLAYTIKA HOLDING and DAX Index.

Diversification Opportunities for PLAYTIKA HOLDING and DAX Index

-0.44

Correlation Coefficient

PLAYTIKA HOLDING  DAX Index

Very good diversification

The 3 months correlation between PLAYTIKA and DAX is -0.44. Overlapping area represents the amount of risk that can be diversified away by holding PLAYTIKA HOLDING DL 01 and DAX Index in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on DAX Index and PLAYTIKA HOLDING 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 PLAYTIKA HOLDING DL 01 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 PLAYTIKA HOLDING i.e., PLAYTIKA HOLDING and DAX Index go up and down completely randomly.

Pair Corralation between PLAYTIKA HOLDING and DAX Index

Assuming the 90 days horizon PLAYTIKA HOLDING DL 01 is expected to under-perform the DAX Index. In addition to that, PLAYTIKA HOLDING is 2.28 times more volatile than DAX Index. It trades about -0.43 of its total potential returns per unit of risk. DAX Index is currently generating about 0.15 per unit of volatility. If you would invest  2,142,824  in DAX Index on December 5, 2024 and sell it today you would earn a total of  89,857  from holding DAX Index or generate 4.19% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Against
Strength	Very Weak
Accuracy	100.0%
Values	Daily Returns

PLAYTIKA HOLDING DL 01  vs.  DAX Index

Pair Trading with PLAYTIKA HOLDING and DAX Index

The main advantage of trading using opposite PLAYTIKA HOLDING and DAX Index positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if PLAYTIKA HOLDING 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 PLAYTIKA HOLDING DL 01 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.

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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.