Correlation Between DATALOGIC and S A P

Can any of the company-specific risk be diversified away by investing in both DATALOGIC and S A P 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 DATALOGIC and S A P into the same portfolio, which is an essential part of the fundamental portfolio management process.

By analyzing existing cross correlation between DATALOGIC and SAP SE, you can compare the effects of market volatilities on DATALOGIC and S A P 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 DATALOGIC with a short position of S A P. Check out your portfolio center. Please also check ongoing floating volatility patterns of DATALOGIC and S A P.

Diversification Opportunities for DATALOGIC and S A P

0.76

Correlation Coefficient

DATALOGIC  S A P

Poor diversification

The 3 months correlation between DATALOGIC and SAP is 0.76. Overlapping area represents the amount of risk that can be diversified away by holding DATALOGIC and SAP SE in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SAP SE and DATALOGIC 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 DATALOGIC are associated (or correlated) with S A P. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SAP SE has no effect on the direction of DATALOGIC i.e., DATALOGIC and S A P go up and down completely randomly.

Pair Corralation between DATALOGIC and S A P

Assuming the 90 days trading horizon DATALOGIC is expected to generate 1.22 times less return on investment than S A P. In addition to that, DATALOGIC is 1.07 times more volatile than SAP SE. It trades about 0.14 of its total potential returns per unit of risk. SAP SE is currently generating about 0.18 per unit of volatility. If you would invest  21,985  in SAP SE on April 20, 2025 and sell it today you would earn a total of  4,330  from holding SAP SE or generate 19.7% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Together
Strength	Significant
Accuracy	98.44%
Values	Daily Returns

DATALOGIC  vs.  SAP SE

DATALOGIC

Risk-Adjusted Performance

OK

Compared to the overall equity markets, risk-adjusted returns on investments in DATALOGIC are ranked lower than 10 (%) of all global equities and portfolios over the last 90 days. In spite of rather fragile technical and fundamental indicators, DATALOGIC exhibited solid returns over the last few months and may actually be approaching a breakup point.

SAP SE

Risk-Adjusted Performance

Good

Compared to the overall equity markets, risk-adjusted returns on investments in SAP SE are ranked lower than 13 (%) of all global equities and portfolios over the last 90 days. Despite nearly uncertain basic indicators, S A P reported solid returns over the last few months and may actually be approaching a breakup point.

Pair Trading with DATALOGIC and S A P

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

The idea behind DATALOGIC and SAP SE 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.