Correlation Between GM and ENGIE ADR1
Can any of the company-specific risk be diversified away by investing in both GM and ENGIE ADR1 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 GM and ENGIE ADR1 into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between General Motors and ENGIE ADR1 EO, you can compare the effects of market volatilities on GM and ENGIE ADR1 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 ENGIE ADR1. Check out your portfolio center. Please also check ongoing floating volatility patterns of GM and ENGIE ADR1.
Diversification Opportunities for GM and ENGIE ADR1
-0.44 | Correlation Coefficient |
Very good diversification
The 3 months correlation between GM and ENGIE is -0.44. Overlapping area represents the amount of risk that can be diversified away by holding General Motors and ENGIE ADR1 EO in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on ENGIE ADR1 EO 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 ENGIE ADR1. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of ENGIE ADR1 EO has no effect on the direction of GM i.e., GM and ENGIE ADR1 go up and down completely randomly.
Pair Corralation between GM and ENGIE ADR1
Allowing for the 90-day total investment horizon General Motors is expected to generate 1.36 times more return on investment than ENGIE ADR1. However, GM is 1.36 times more volatile than ENGIE ADR1 EO. It trades about 0.05 of its potential returns per unit of risk. ENGIE ADR1 EO is currently generating about 0.04 per unit of risk. If you would invest 3,397 in General Motors on September 25, 2024 and sell it today you would earn a total of 1,954 from holding General Motors or generate 57.52% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 98.22% |
Values | Daily Returns |
General Motors vs. ENGIE ADR1 EO
Performance |
Timeline |
General Motors |
ENGIE ADR1 EO |
GM and ENGIE ADR1 Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with GM and ENGIE ADR1
The main advantage of trading using opposite GM and ENGIE ADR1 positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GM position performs unexpectedly, ENGIE ADR1 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 ENGIE ADR1 will offset losses from the drop in ENGIE ADR1's long position.The idea behind General Motors and ENGIE ADR1 EO 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.ENGIE ADR1 vs. Iberdrola SA | ENGIE ADR1 vs. Enel SpA | ENGIE ADR1 vs. Enel SpA | ENGIE ADR1 vs. National Grid PLC |
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 Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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