Correlation Between Data Modul and Pacific Basin
Can any of the company-specific risk be diversified away by investing in both Data Modul and Pacific Basin 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 Data Modul and Pacific Basin into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Data Modul AG and Pacific Basin Shipping, you can compare the effects of market volatilities on Data Modul and Pacific Basin 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 Data Modul with a short position of Pacific Basin. Check out your portfolio center. Please also check ongoing floating volatility patterns of Data Modul and Pacific Basin.
Diversification Opportunities for Data Modul and Pacific Basin
-0.08 | Correlation Coefficient |
Good diversification
The 3 months correlation between Data and Pacific is -0.08. Overlapping area represents the amount of risk that can be diversified away by holding Data Modul AG and Pacific Basin Shipping in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Pacific Basin Shipping and Data Modul 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 Data Modul AG are associated (or correlated) with Pacific Basin. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Pacific Basin Shipping has no effect on the direction of Data Modul i.e., Data Modul and Pacific Basin go up and down completely randomly.
Pair Corralation between Data Modul and Pacific Basin
Assuming the 90 days trading horizon Data Modul AG is expected to generate 0.8 times more return on investment than Pacific Basin. However, Data Modul AG is 1.24 times less risky than Pacific Basin. It trades about -0.09 of its potential returns per unit of risk. Pacific Basin Shipping is currently generating about -0.21 per unit of risk. If you would invest 2,840 in Data Modul AG on October 9, 2024 and sell it today you would lose (240.00) from holding Data Modul AG or give up 8.45% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 97.37% |
Values | Daily Returns |
Data Modul AG vs. Pacific Basin Shipping
Performance |
Timeline |
Data Modul AG |
Pacific Basin Shipping |
Data Modul and Pacific Basin Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Data Modul and Pacific Basin
The main advantage of trading using opposite Data Modul and Pacific Basin positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Data Modul position performs unexpectedly, Pacific Basin 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 Pacific Basin will offset losses from the drop in Pacific Basin's long position.The idea behind Data Modul AG and Pacific Basin Shipping 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.Pacific Basin vs. DEVRY EDUCATION GRP | Pacific Basin vs. SIEM OFFSHORE NEW | Pacific Basin vs. Xinhua Winshare Publishing | Pacific Basin vs. GigaMedia |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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