Correlation Between PACCAR and ServiceNow
Can any of the company-specific risk be diversified away by investing in both PACCAR and ServiceNow 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 PACCAR and ServiceNow into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between PACCAR Inc and ServiceNow, you can compare the effects of market volatilities on PACCAR and ServiceNow 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 PACCAR with a short position of ServiceNow. Check out your portfolio center. Please also check ongoing floating volatility patterns of PACCAR and ServiceNow.
Diversification Opportunities for PACCAR and ServiceNow
0.37 | Correlation Coefficient |
Weak diversification
The 3 months correlation between PACCAR and ServiceNow is 0.37. Overlapping area represents the amount of risk that can be diversified away by holding PACCAR Inc and ServiceNow in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on ServiceNow and PACCAR 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 PACCAR Inc are associated (or correlated) with ServiceNow. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of ServiceNow has no effect on the direction of PACCAR i.e., PACCAR and ServiceNow go up and down completely randomly.
Pair Corralation between PACCAR and ServiceNow
Given the investment horizon of 90 days PACCAR Inc is expected to generate 0.57 times more return on investment than ServiceNow. However, PACCAR Inc is 1.74 times less risky than ServiceNow. It trades about -0.06 of its potential returns per unit of risk. ServiceNow is currently generating about -0.07 per unit of risk. If you would invest 11,264 in PACCAR Inc on December 2, 2024 and sell it today you would lose (540.00) from holding PACCAR Inc or give up 4.79% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
PACCAR Inc vs. ServiceNow
Performance |
Timeline |
PACCAR Inc |
ServiceNow |
PACCAR and ServiceNow Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with PACCAR and ServiceNow
The main advantage of trading using opposite PACCAR and ServiceNow positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if PACCAR position performs unexpectedly, ServiceNow 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 ServiceNow will offset losses from the drop in ServiceNow's long position.The idea behind PACCAR Inc and ServiceNow 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.ServiceNow vs. Autodesk | ServiceNow vs. Intuit Inc | ServiceNow vs. Zoom Video Communications | ServiceNow vs. Snowflake |
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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