Correlation Between GM and Parkland
Can any of the company-specific risk be diversified away by investing in both GM and Parkland 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 Parkland into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between General Motors and Parkland, you can compare the effects of market volatilities on GM and Parkland 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 Parkland. Check out your portfolio center. Please also check ongoing floating volatility patterns of GM and Parkland.
Diversification Opportunities for GM and Parkland
Excellent diversification
The 3 months correlation between GM and Parkland is -0.53. Overlapping area represents the amount of risk that can be diversified away by holding General Motors and Parkland in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Parkland 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 Parkland. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Parkland has no effect on the direction of GM i.e., GM and Parkland go up and down completely randomly.
Pair Corralation between GM and Parkland
Allowing for the 90-day total investment horizon General Motors is expected to under-perform the Parkland. But the stock apears to be less risky and, when comparing its historical volatility, General Motors is 1.3 times less risky than Parkland. The stock trades about -0.31 of its potential returns per unit of risk. The Parkland is currently generating about -0.12 of returns per unit of risk over similar time horizon. If you would invest 2,468 in Parkland on September 24, 2024 and sell it today you would lose (195.00) from holding Parkland or give up 7.9% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
General Motors vs. Parkland
Performance |
Timeline |
General Motors |
Parkland |
GM and Parkland Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with GM and Parkland
The main advantage of trading using opposite GM and Parkland positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GM position performs unexpectedly, Parkland 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 Parkland will offset losses from the drop in Parkland's long position.The idea behind General Motors and Parkland 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.Parkland vs. Meso Numismatics | Parkland vs. Tandy Leather Factory | Parkland vs. EVgo Equity Warrants | Parkland vs. Sally Beauty Holdings |
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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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