Correlation Between GM and Nordea 1
Specify exactly 2 symbols:
By analyzing existing cross correlation between General Motors and Nordea 1 , you can compare the effects of market volatilities on GM and Nordea 1 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 GM with a short position of Nordea 1. Check out your portfolio center. Please also check ongoing floating volatility patterns of GM and Nordea 1.
Diversification Opportunities for GM and Nordea 1
Modest diversification
The 3 months correlation between GM and Nordea is 0.25. Overlapping area represents the amount of risk that can be diversified away by holding General Motors and Nordea 1 in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Nordea 1 and GM 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 General Motors are associated (or correlated) with Nordea 1. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Nordea 1 has no effect on the direction of GM i.e., GM and Nordea 1 go up and down completely randomly.
Pair Corralation between GM and Nordea 1
Allowing for the 90-day total investment horizon General Motors is expected to under-perform the Nordea 1. In addition to that, GM is 2.51 times more volatile than Nordea 1 . It trades about -0.08 of its total potential returns per unit of risk. Nordea 1 is currently generating about 0.12 per unit of volatility. If you would invest 39,995 in Nordea 1 on October 22, 2024 and sell it today you would earn a total of 587.00 from holding Nordea 1 or generate 1.47% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 89.47% |
Values | Daily Returns |
General Motors vs. Nordea 1
Performance |
Timeline |
General Motors |
Nordea 1 |
GM and Nordea 1 Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with GM and Nordea 1
The main advantage of trading using opposite GM and Nordea 1 positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GM position performs unexpectedly, Nordea 1 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 Nordea 1 will offset losses from the drop in Nordea 1's long position.The idea behind General Motors and Nordea 1 pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.Nordea 1 vs. Nordea 1 | Nordea 1 vs. Nordea Norwegian Stars | Nordea 1 vs. Nordea North American | Nordea 1 vs. Nordea 1 |
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 Idea Optimizer module to use advanced portfolio builder with pre-computed micro ideas to build optimal portfolio .
Other Complementary Tools
CEOs Directory Screen CEOs from public companies around the world | |
Portfolio Rebalancing Analyze risk-adjusted returns against different time horizons to find asset-allocation targets | |
Volatility Analysis Get historical volatility and risk analysis based on latest market data | |
Commodity Directory Find actively traded commodities issued by global exchanges | |
Equity Valuation Check real value of public entities based on technical and fundamental data |