Correlation Between MOL Nyrt and Budapesti Ingatlan
Can any of the company-specific risk be diversified away by investing in both MOL Nyrt and Budapesti Ingatlan 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 MOL Nyrt and Budapesti Ingatlan into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between MOL Nyrt and Budapesti Ingatlan Hasznositasi, you can compare the effects of market volatilities on MOL Nyrt and Budapesti Ingatlan 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 MOL Nyrt with a short position of Budapesti Ingatlan. Check out your portfolio center. Please also check ongoing floating volatility patterns of MOL Nyrt and Budapesti Ingatlan.
Diversification Opportunities for MOL Nyrt and Budapesti Ingatlan
0.19 | Correlation Coefficient |
Average diversification
The 3 months correlation between MOL and Budapesti is 0.19. Overlapping area represents the amount of risk that can be diversified away by holding MOL Nyrt and Budapesti Ingatlan Hasznositas in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Budapesti Ingatlan and MOL Nyrt 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 MOL Nyrt are associated (or correlated) with Budapesti Ingatlan. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Budapesti Ingatlan has no effect on the direction of MOL Nyrt i.e., MOL Nyrt and Budapesti Ingatlan go up and down completely randomly.
Pair Corralation between MOL Nyrt and Budapesti Ingatlan
Assuming the 90 days trading horizon MOL Nyrt is expected to generate 0.83 times more return on investment than Budapesti Ingatlan. However, MOL Nyrt is 1.2 times less risky than Budapesti Ingatlan. It trades about 0.59 of its potential returns per unit of risk. Budapesti Ingatlan Hasznositasi is currently generating about 0.35 per unit of risk. If you would invest 266,800 in MOL Nyrt on October 20, 2024 and sell it today you would earn a total of 21,800 from holding MOL Nyrt or generate 8.17% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
MOL Nyrt vs. Budapesti Ingatlan Hasznositas
Performance |
Timeline |
MOL Nyrt |
Budapesti Ingatlan |
MOL Nyrt and Budapesti Ingatlan Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with MOL Nyrt and Budapesti Ingatlan
The main advantage of trading using opposite MOL Nyrt and Budapesti Ingatlan positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if MOL Nyrt position performs unexpectedly, Budapesti Ingatlan 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 Budapesti Ingatlan will offset losses from the drop in Budapesti Ingatlan's long position.MOL Nyrt vs. OPUS GLOBAL Nyrt | MOL Nyrt vs. OTP Bank Nyrt | MOL Nyrt vs. Infineon Technologies AG | MOL Nyrt vs. Appeninn Nyrt |
Budapesti Ingatlan vs. CIG Pannonia Life | Budapesti Ingatlan vs. Infineon Technologies AG | Budapesti Ingatlan vs. AKKO Invest Nyrt | Budapesti Ingatlan vs. Deutsche Lufthansa AG |
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 Suggestion module to get suggestions outside of your existing asset allocation including your own model portfolios.
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