Correlation Between Raba Jarmuipari and BASF SE
Can any of the company-specific risk be diversified away by investing in both Raba Jarmuipari and BASF SE 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 Raba Jarmuipari and BASF SE into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Raba Jarmuipari Holding and BASF SE, you can compare the effects of market volatilities on Raba Jarmuipari and BASF SE 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 Raba Jarmuipari with a short position of BASF SE. Check out your portfolio center. Please also check ongoing floating volatility patterns of Raba Jarmuipari and BASF SE.
Diversification Opportunities for Raba Jarmuipari and BASF SE
-0.07 | Correlation Coefficient |
Good diversification
The 3 months correlation between Raba and BASF is -0.07. Overlapping area represents the amount of risk that can be diversified away by holding Raba Jarmuipari Holding and BASF SE in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BASF SE and Raba Jarmuipari 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 Raba Jarmuipari Holding are associated (or correlated) with BASF SE. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of BASF SE has no effect on the direction of Raba Jarmuipari i.e., Raba Jarmuipari and BASF SE go up and down completely randomly.
Pair Corralation between Raba Jarmuipari and BASF SE
Assuming the 90 days trading horizon Raba Jarmuipari is expected to generate 8.18 times less return on investment than BASF SE. But when comparing it to its historical volatility, Raba Jarmuipari Holding is 1.42 times less risky than BASF SE. It trades about 0.01 of its potential returns per unit of risk. BASF SE is currently generating about 0.06 of returns per unit of risk over similar time horizon. If you would invest 1,799,400 in BASF SE on September 15, 2024 and sell it today you would earn a total of 65,000 from holding BASF SE or generate 3.61% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 48.28% |
Values | Daily Returns |
Raba Jarmuipari Holding vs. BASF SE
Performance |
Timeline |
Raba Jarmuipari Holding |
BASF SE |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Insignificant
Raba Jarmuipari and BASF SE Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Raba Jarmuipari and BASF SE
The main advantage of trading using opposite Raba Jarmuipari and BASF SE positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Raba Jarmuipari position performs unexpectedly, BASF SE 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 BASF SE will offset losses from the drop in BASF SE's long position.Raba Jarmuipari vs. Infineon Technologies AG | Raba Jarmuipari vs. AKKO Invest Nyrt | Raba Jarmuipari vs. Deutsche Lufthansa AG | Raba Jarmuipari vs. ALTEO Energiaszolgaltato Nyrt |
BASF SE vs. OTP Bank Nyrt | BASF SE vs. MOL Nyrt | BASF SE vs. OPUS GLOBAL Nyrt | BASF SE vs. ALTEO Energiaszolgaltato Nyrt |
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.
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