Correlation Between GM and Value Line
Can any of the company-specific risk be diversified away by investing in both GM and Value Line 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 Value Line into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between General Motors and Value Line E, you can compare the effects of market volatilities on GM and Value Line 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 Value Line. Check out your portfolio center. Please also check ongoing floating volatility patterns of GM and Value Line.
Diversification Opportunities for GM and Value Line
-0.85 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between GM and Value is -0.85. Overlapping area represents the amount of risk that can be diversified away by holding General Motors and Value Line E in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Value Line E 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 Value Line. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Value Line E has no effect on the direction of GM i.e., GM and Value Line go up and down completely randomly.
Pair Corralation between GM and Value Line
Allowing for the 90-day total investment horizon General Motors is expected to generate 5.07 times more return on investment than Value Line. However, GM is 5.07 times more volatile than Value Line E. It trades about 0.05 of its potential returns per unit of risk. Value Line E is currently generating about 0.02 per unit of risk. If you would invest 3,807 in General Motors on August 26, 2024 and sell it today you would earn a total of 2,046 from holding General Motors or generate 53.74% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
General Motors vs. Value Line E
Performance |
| Timeline |
| General Motors |
| Value Line E |
GM and Value Line Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with GM and Value Line
The main advantage of trading using opposite GM and Value Line positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GM position performs unexpectedly, Value Line 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 Value Line will offset losses from the drop in Value Line's long position.The idea behind General Motors and Value Line E 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.| Value Line vs. Value Line Income | Value Line vs. Value Line Larger | Value Line vs. Ab Sustainable Thematic | Value Line vs. Value Line Mid |
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 Competition Analyzer module to analyze and compare many basic indicators for a group of related or unrelated entities.
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