Correlation Between Tecnotree Oyj and Oma Saastopankki
Can any of the company-specific risk be diversified away by investing in both Tecnotree Oyj and Oma Saastopankki 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 Tecnotree Oyj and Oma Saastopankki into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Tecnotree Oyj and Oma Saastopankki Oyj, you can compare the effects of market volatilities on Tecnotree Oyj and Oma Saastopankki 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 Tecnotree Oyj with a short position of Oma Saastopankki. Check out your portfolio center. Please also check ongoing floating volatility patterns of Tecnotree Oyj and Oma Saastopankki.
Diversification Opportunities for Tecnotree Oyj and Oma Saastopankki
0.71 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Tecnotree and Oma is 0.71. Overlapping area represents the amount of risk that can be diversified away by holding Tecnotree Oyj and Oma Saastopankki Oyj in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Oma Saastopankki Oyj and Tecnotree Oyj 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 Tecnotree Oyj are associated (or correlated) with Oma Saastopankki. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Oma Saastopankki Oyj has no effect on the direction of Tecnotree Oyj i.e., Tecnotree Oyj and Oma Saastopankki go up and down completely randomly.
Pair Corralation between Tecnotree Oyj and Oma Saastopankki
Assuming the 90 days trading horizon Tecnotree Oyj is expected to under-perform the Oma Saastopankki. In addition to that, Tecnotree Oyj is 1.1 times more volatile than Oma Saastopankki Oyj. It trades about -0.2 of its total potential returns per unit of risk. Oma Saastopankki Oyj is currently generating about -0.16 per unit of volatility. If you would invest 1,424 in Oma Saastopankki Oyj on August 31, 2024 and sell it today you would lose (332.00) from holding Oma Saastopankki Oyj or give up 23.31% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Tecnotree Oyj vs. Oma Saastopankki Oyj
Performance |
Timeline |
Tecnotree Oyj |
Oma Saastopankki Oyj |
Tecnotree Oyj and Oma Saastopankki Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Tecnotree Oyj and Oma Saastopankki
The main advantage of trading using opposite Tecnotree Oyj and Oma Saastopankki positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Tecnotree Oyj position performs unexpectedly, Oma Saastopankki 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 Oma Saastopankki will offset losses from the drop in Oma Saastopankki's long position.Tecnotree Oyj vs. Harvia Oyj | Tecnotree Oyj vs. Qt Group Oyj | Tecnotree Oyj vs. Kamux Suomi Oy | Tecnotree Oyj vs. Tokmanni Group Oyj |
Oma Saastopankki vs. Kamux Suomi Oy | Oma Saastopankki vs. Harvia Oyj | Oma Saastopankki vs. TietoEVRY Corp | Oma Saastopankki vs. Tokmanni Group 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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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