Correlation Between GM and Korn Ferry
Can any of the company-specific risk be diversified away by investing in both GM and Korn Ferry 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 Korn Ferry into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between General Motors and Korn Ferry, you can compare the effects of market volatilities on GM and Korn Ferry 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 Korn Ferry. Check out your portfolio center. Please also check ongoing floating volatility patterns of GM and Korn Ferry.
Diversification Opportunities for GM and Korn Ferry
0.5 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between GM and Korn is 0.5. Overlapping area represents the amount of risk that can be diversified away by holding General Motors and Korn Ferry in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Korn Ferry 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 Korn Ferry. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Korn Ferry has no effect on the direction of GM i.e., GM and Korn Ferry go up and down completely randomly.
Pair Corralation between GM and Korn Ferry
Allowing for the 90-day total investment horizon General Motors is expected to under-perform the Korn Ferry. In addition to that, GM is 1.49 times more volatile than Korn Ferry. It trades about -0.02 of its total potential returns per unit of risk. Korn Ferry is currently generating about 0.01 per unit of volatility. If you would invest 6,826 in Korn Ferry on December 25, 2024 and sell it today you would earn a total of 0.00 from holding Korn Ferry or generate 0.0% 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. Korn Ferry
Performance |
Timeline |
General Motors |
Korn Ferry |
GM and Korn Ferry Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with GM and Korn Ferry
The main advantage of trading using opposite GM and Korn Ferry positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GM position performs unexpectedly, Korn Ferry 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 Korn Ferry will offset losses from the drop in Korn Ferry's long position.The idea behind General Motors and Korn Ferry 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.Korn Ferry vs. Heidrick Struggles International | Korn Ferry vs. Kelly Services A | Korn Ferry vs. Kforce Inc | Korn Ferry vs. ManpowerGroup |
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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