Correlation Between GM and SentinelOne
Can any of the company-specific risk be diversified away by investing in both GM and SentinelOne 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 SentinelOne into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between General Motors and SentinelOne, you can compare the effects of market volatilities on GM and SentinelOne 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 SentinelOne. Check out your portfolio center. Please also check ongoing floating volatility patterns of GM and SentinelOne.
Diversification Opportunities for GM and SentinelOne
0.17 | Correlation Coefficient |
Average diversification
The 3 months correlation between GM and SentinelOne is 0.17. Overlapping area represents the amount of risk that can be diversified away by holding General Motors and SentinelOne in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SentinelOne 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 SentinelOne. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SentinelOne has no effect on the direction of GM i.e., GM and SentinelOne go up and down completely randomly.
Pair Corralation between GM and SentinelOne
Allowing for the 90-day total investment horizon General Motors is expected to generate 1.07 times more return on investment than SentinelOne. However, GM is 1.07 times more volatile than SentinelOne. It trades about -0.03 of its potential returns per unit of risk. SentinelOne is currently generating about -0.07 per unit of risk. If you would invest 5,414 in General Motors on December 27, 2024 and sell it today you would lose (319.00) from holding General Motors or give up 5.89% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
General Motors vs. SentinelOne
Performance |
Timeline |
General Motors |
SentinelOne |
GM and SentinelOne Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with GM and SentinelOne
The main advantage of trading using opposite GM and SentinelOne positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if GM position performs unexpectedly, SentinelOne 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 SentinelOne will offset losses from the drop in SentinelOne's long position.The idea behind General Motors and SentinelOne 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.SentinelOne vs. Palo Alto Networks | SentinelOne vs. Adobe Systems Incorporated | SentinelOne vs. Crowdstrike Holdings | SentinelOne vs. Zscaler |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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