Correlation Between Faraday Future and GM
Can any of the company-specific risk be diversified away by investing in both Faraday Future and GM 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 Faraday Future and GM into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Faraday Future Intelligent and General Motors, you can compare the effects of market volatilities on Faraday Future and GM 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 Faraday Future with a short position of GM. Check out your portfolio center. Please also check ongoing floating volatility patterns of Faraday Future and GM.
Diversification Opportunities for Faraday Future and GM
-0.13 | Correlation Coefficient |
Good diversification
The 3 months correlation between Faraday and GM is -0.13. Overlapping area represents the amount of risk that can be diversified away by holding Faraday Future Intelligent and General Motors in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on General Motors and Faraday Future 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 Faraday Future Intelligent are associated (or correlated) with GM. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of General Motors has no effect on the direction of Faraday Future i.e., Faraday Future and GM go up and down completely randomly.
Pair Corralation between Faraday Future and GM
Given the investment horizon of 90 days Faraday Future Intelligent is expected to under-perform the GM. In addition to that, Faraday Future is 2.87 times more volatile than General Motors. It trades about -0.59 of its total potential returns per unit of risk. General Motors is currently generating about -0.04 per unit of volatility. If you would invest 5,137 in General Motors on November 2, 2024 and sell it today you would lose (159.00) from holding General Motors or give up 3.1% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Faraday Future Intelligent vs. General Motors
Performance |
| Timeline |
| Faraday Future Intel |
| General Motors |
Faraday Future and GM Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Faraday Future and GM
The main advantage of trading using opposite Faraday Future and GM positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Faraday Future position performs unexpectedly, GM 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 GM will offset losses from the drop in GM's long position.The idea behind Faraday Future Intelligent and General Motors 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.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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