Correlation Between GM and Helen Of
Can any of the company-specific risk be diversified away by investing in both GM and Helen Of 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 Helen Of into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between General Motors and Helen of Troy, you can compare the effects of market volatilities on GM and Helen Of 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 Helen Of. Check out your portfolio center. Please also check ongoing floating volatility patterns of GM and Helen Of.
Diversification Opportunities for GM and Helen Of
Very weak diversification
The 3 months correlation between GM and Helen is 0.51. Overlapping area represents the amount of risk that can be diversified away by holding General Motors and Helen of Troy in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Helen of Troy 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 Helen Of. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Helen of Troy has no effect on the direction of GM i.e., GM and Helen Of go up and down completely randomly.
Pair Corralation between GM and Helen Of
Allowing for the 90-day total investment horizon GM is expected to generate 1.7 times less return on investment than Helen Of. In addition to that, GM is 1.4 times more volatile than Helen of Troy. It trades about 0.12 of its total potential returns per unit of risk. Helen of Troy is currently generating about 0.28 per unit of volatility. If you would invest 6,421 in Helen of Troy on August 31, 2024 and sell it today you would earn a total of 830.00 from holding Helen of Troy or generate 12.93% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
General Motors vs. Helen of Troy
Performance |
| Timeline |
| General Motors |
| Helen of Troy |
GM and Helen Of Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with GM and Helen Of
The main advantage of trading using opposite GM and Helen Of positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GM position performs unexpectedly, Helen Of 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 Helen Of will offset losses from the drop in Helen Of's long position.The idea behind General Motors and Helen of Troy 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.| Helen Of vs. Inter Parfums | Helen Of vs. J J Snack | Helen Of vs. Lancaster Colony | Helen Of vs. Dorman Products |
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 Risk-Return Analysis module to view associations between returns expected from investment and the risk you assume.
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