Correlation Between Budapesti Ingatlan and MOL Nyrt
Can any of the company-specific risk be diversified away by investing in both Budapesti Ingatlan and MOL Nyrt 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 Budapesti Ingatlan and MOL Nyrt into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Budapesti Ingatlan Hasznositasi and MOL Nyrt, you can compare the effects of market volatilities on Budapesti Ingatlan and MOL Nyrt 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 Budapesti Ingatlan with a short position of MOL Nyrt. Check out your portfolio center. Please also check ongoing floating volatility patterns of Budapesti Ingatlan and MOL Nyrt.
Diversification Opportunities for Budapesti Ingatlan and MOL Nyrt
-0.02 | Correlation Coefficient |
Good diversification
The 3 months correlation between Budapesti and MOL is -0.02. Overlapping area represents the amount of risk that can be diversified away by holding Budapesti Ingatlan Hasznositas and MOL Nyrt in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on MOL Nyrt and Budapesti Ingatlan 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 Budapesti Ingatlan Hasznositasi are associated (or correlated) with MOL Nyrt. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of MOL Nyrt has no effect on the direction of Budapesti Ingatlan i.e., Budapesti Ingatlan and MOL Nyrt go up and down completely randomly.
Pair Corralation between Budapesti Ingatlan and MOL Nyrt
Assuming the 90 days trading horizon Budapesti Ingatlan Hasznositasi is expected to generate 1.92 times more return on investment than MOL Nyrt. However, Budapesti Ingatlan is 1.92 times more volatile than MOL Nyrt. It trades about 0.07 of its potential returns per unit of risk. MOL Nyrt is currently generating about 0.05 per unit of risk. If you would invest 47,000 in Budapesti Ingatlan Hasznositasi on September 15, 2024 and sell it today you would earn a total of 3,200 from holding Budapesti Ingatlan Hasznositasi or generate 6.81% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Budapesti Ingatlan Hasznositas vs. MOL Nyrt
Performance |
Timeline |
Budapesti Ingatlan |
MOL Nyrt |
Budapesti Ingatlan and MOL Nyrt Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Budapesti Ingatlan and MOL Nyrt
The main advantage of trading using opposite Budapesti Ingatlan and MOL Nyrt positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Budapesti Ingatlan position performs unexpectedly, MOL Nyrt 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 MOL Nyrt will offset losses from the drop in MOL Nyrt's long position.Budapesti Ingatlan vs. CIG Pannonia Life | Budapesti Ingatlan vs. Infineon Technologies AG | Budapesti Ingatlan vs. AKKO Invest Nyrt | Budapesti Ingatlan vs. Deutsche Lufthansa AG |
MOL Nyrt vs. NordTelekom Telecommunications Service | MOL Nyrt vs. Deutsche Bank AG | MOL Nyrt vs. Commerzbank 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 Alpha Finder module to use alpha and beta coefficients to find investment opportunities after accounting for the risk.
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