Correlation Between GM and GOOD BUILDINGS
Can any of the company-specific risk be diversified away by investing in both GM and GOOD BUILDINGS 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 GOOD BUILDINGS into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between General Motors and GOOD BUILDINGS Swiss, you can compare the effects of market volatilities on GM and GOOD BUILDINGS 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 GOOD BUILDINGS. Check out your portfolio center. Please also check ongoing floating volatility patterns of GM and GOOD BUILDINGS.
Diversification Opportunities for GM and GOOD BUILDINGS
-0.08 | Correlation Coefficient |
Good diversification
The 3 months correlation between GM and GOOD is -0.08. Overlapping area represents the amount of risk that can be diversified away by holding General Motors and GOOD BUILDINGS Swiss in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on GOOD BUILDINGS Swiss 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 GOOD BUILDINGS. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of GOOD BUILDINGS Swiss has no effect on the direction of GM i.e., GM and GOOD BUILDINGS go up and down completely randomly.
Pair Corralation between GM and GOOD BUILDINGS
Allowing for the 90-day total investment horizon General Motors is expected to generate 3.26 times more return on investment than GOOD BUILDINGS. However, GM is 3.26 times more volatile than GOOD BUILDINGS Swiss. It trades about 0.05 of its potential returns per unit of risk. GOOD BUILDINGS Swiss is currently generating about 0.07 per unit of risk. If you would invest 3,902 in General Motors on September 30, 2024 and sell it today you would earn a total of 1,526 from holding General Motors or generate 39.11% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 98.66% |
Values | Daily Returns |
General Motors vs. GOOD BUILDINGS Swiss
Performance |
Timeline |
General Motors |
GOOD BUILDINGS Swiss |
GM and GOOD BUILDINGS Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with GM and GOOD BUILDINGS
The main advantage of trading using opposite GM and GOOD BUILDINGS positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GM position performs unexpectedly, GOOD BUILDINGS 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 GOOD BUILDINGS will offset losses from the drop in GOOD BUILDINGS's long position.The idea behind General Motors and GOOD BUILDINGS Swiss 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 Volatility Analysis module to get historical volatility and risk analysis based on latest market data.
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