Correlation Between Oma Saastopankki and Oriola KD
Can any of the company-specific risk be diversified away by investing in both Oma Saastopankki and Oriola KD 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 Oma Saastopankki and Oriola KD into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Oma Saastopankki Oyj and Oriola KD Oyj A, you can compare the effects of market volatilities on Oma Saastopankki and Oriola KD 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 Oma Saastopankki with a short position of Oriola KD. Check out your portfolio center. Please also check ongoing floating volatility patterns of Oma Saastopankki and Oriola KD.
Diversification Opportunities for Oma Saastopankki and Oriola KD
0.6 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Oma and Oriola is 0.6. Overlapping area represents the amount of risk that can be diversified away by holding Oma Saastopankki Oyj and Oriola KD Oyj A in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Oriola KD Oyj and Oma Saastopankki 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 Oma Saastopankki Oyj are associated (or correlated) with Oriola KD. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Oriola KD Oyj has no effect on the direction of Oma Saastopankki i.e., Oma Saastopankki and Oriola KD go up and down completely randomly.
Pair Corralation between Oma Saastopankki and Oriola KD
Assuming the 90 days trading horizon Oma Saastopankki is expected to generate 1.74 times less return on investment than Oriola KD. In addition to that, Oma Saastopankki is 1.66 times more volatile than Oriola KD Oyj A. It trades about 0.05 of its total potential returns per unit of risk. Oriola KD Oyj A is currently generating about 0.14 per unit of volatility. If you would invest 92.00 in Oriola KD Oyj A on October 5, 2024 and sell it today you would earn a total of 3.00 from holding Oriola KD Oyj A or generate 3.26% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Oma Saastopankki Oyj vs. Oriola KD Oyj A
Performance |
Timeline |
Oma Saastopankki Oyj |
Oriola KD Oyj |
Oma Saastopankki and Oriola KD Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Oma Saastopankki and Oriola KD
The main advantage of trading using opposite Oma Saastopankki and Oriola KD positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Oma Saastopankki position performs unexpectedly, Oriola KD 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 Oriola KD will offset losses from the drop in Oriola KD's long position.Oma Saastopankki vs. Kamux Suomi Oy | Oma Saastopankki vs. Harvia Oyj | Oma Saastopankki vs. TietoEVRY Corp | Oma Saastopankki vs. Tokmanni Group Oyj |
Oriola KD vs. Oriola KD Oyj B | Oriola KD vs. Vaisala Oyj A | Oriola KD vs. KONE Oyj | Oriola KD vs. Boreo Oyj |
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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