Correlation Between Apple and Data Modul
Can any of the company-specific risk be diversified away by investing in both Apple and Data Modul 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 Apple and Data Modul into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Apple Inc and Data Modul AG, you can compare the effects of market volatilities on Apple and Data Modul 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 Apple with a short position of Data Modul. Check out your portfolio center. Please also check ongoing floating volatility patterns of Apple and Data Modul.
Diversification Opportunities for Apple and Data Modul
-0.17 | Correlation Coefficient |
Good diversification
The 3 months correlation between Apple and Data is -0.17. Overlapping area represents the amount of risk that can be diversified away by holding Apple Inc and Data Modul AG in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Data Modul AG and Apple 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 Apple Inc are associated (or correlated) with Data Modul. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Data Modul AG has no effect on the direction of Apple i.e., Apple and Data Modul go up and down completely randomly.
Pair Corralation between Apple and Data Modul
Assuming the 90 days trading horizon Apple Inc is expected to generate 0.84 times more return on investment than Data Modul. However, Apple Inc is 1.19 times less risky than Data Modul. It trades about 0.02 of its potential returns per unit of risk. Data Modul AG is currently generating about -0.02 per unit of risk. If you would invest 17,978 in Apple Inc on April 23, 2025 and sell it today you would earn a total of 176.00 from holding Apple Inc or generate 0.98% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Apple Inc vs. Data Modul AG
Performance |
Timeline |
Apple Inc |
Data Modul AG |
Apple and Data Modul Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Apple and Data Modul
The main advantage of trading using opposite Apple and Data Modul positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Apple position performs unexpectedly, Data Modul 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 Data Modul will offset losses from the drop in Data Modul's long position.The idea behind Apple Inc and Data Modul AG 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.Data Modul vs. FIREWEED METALS P | Data Modul vs. Lion One Metals | Data Modul vs. Coeur Mining | Data Modul vs. GREENX METALS LTD |
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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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