Correlation Between Nokia Oyj and Lassila Tikanoja
Can any of the company-specific risk be diversified away by investing in both Nokia Oyj and Lassila Tikanoja 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 Nokia Oyj and Lassila Tikanoja into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Nokia Oyj and Lassila Tikanoja Oyj, you can compare the effects of market volatilities on Nokia Oyj and Lassila Tikanoja 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 Nokia Oyj with a short position of Lassila Tikanoja. Check out your portfolio center. Please also check ongoing floating volatility patterns of Nokia Oyj and Lassila Tikanoja.
Diversification Opportunities for Nokia Oyj and Lassila Tikanoja
-0.17 | Correlation Coefficient |
Good diversification
The 3 months correlation between Nokia and Lassila is -0.17. Overlapping area represents the amount of risk that can be diversified away by holding Nokia Oyj and Lassila Tikanoja Oyj in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Lassila Tikanoja Oyj and Nokia 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 Nokia Oyj are associated (or correlated) with Lassila Tikanoja. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Lassila Tikanoja Oyj has no effect on the direction of Nokia Oyj i.e., Nokia Oyj and Lassila Tikanoja go up and down completely randomly.
Pair Corralation between Nokia Oyj and Lassila Tikanoja
Assuming the 90 days trading horizon Nokia Oyj is expected to generate 1.16 times more return on investment than Lassila Tikanoja. However, Nokia Oyj is 1.16 times more volatile than Lassila Tikanoja Oyj. It trades about 0.37 of its potential returns per unit of risk. Lassila Tikanoja Oyj is currently generating about -0.16 per unit of risk. If you would invest 400.00 in Nokia Oyj on October 5, 2024 and sell it today you would earn a total of 29.00 from holding Nokia Oyj or generate 7.25% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Nokia Oyj vs. Lassila Tikanoja Oyj
Performance |
Timeline |
Nokia Oyj |
Lassila Tikanoja Oyj |
Nokia Oyj and Lassila Tikanoja Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Nokia Oyj and Lassila Tikanoja
The main advantage of trading using opposite Nokia Oyj and Lassila Tikanoja positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Nokia Oyj position performs unexpectedly, Lassila Tikanoja 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 Lassila Tikanoja will offset losses from the drop in Lassila Tikanoja's long position.Nokia Oyj vs. Fortum Oyj | Nokia Oyj vs. Nordea Bank Abp | Nokia Oyj vs. Sampo Oyj A | Nokia Oyj vs. Neste Oil Oyj |
Lassila Tikanoja vs. Sampo Oyj A | Lassila Tikanoja vs. Fortum Oyj | Lassila Tikanoja vs. UPM Kymmene Oyj | Lassila Tikanoja vs. Nordea Bank Abp |
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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