Correlation Between Gitlab and Bigcommerce Holdings
Can any of the company-specific risk be diversified away by investing in both Gitlab and Bigcommerce Holdings 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 Gitlab and Bigcommerce Holdings into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Gitlab Inc and Bigcommerce Holdings, you can compare the effects of market volatilities on Gitlab and Bigcommerce Holdings 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 Gitlab with a short position of Bigcommerce Holdings. Check out your portfolio center. Please also check ongoing floating volatility patterns of Gitlab and Bigcommerce Holdings.
Diversification Opportunities for Gitlab and Bigcommerce Holdings
0.65 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Gitlab and Bigcommerce is 0.65. Overlapping area represents the amount of risk that can be diversified away by holding Gitlab Inc and Bigcommerce Holdings in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bigcommerce Holdings and Gitlab 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 Gitlab Inc are associated (or correlated) with Bigcommerce Holdings. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bigcommerce Holdings has no effect on the direction of Gitlab i.e., Gitlab and Bigcommerce Holdings go up and down completely randomly.
Pair Corralation between Gitlab and Bigcommerce Holdings
Given the investment horizon of 90 days Gitlab is expected to generate 3.0 times less return on investment than Bigcommerce Holdings. But when comparing it to its historical volatility, Gitlab Inc is 1.73 times less risky than Bigcommerce Holdings. It trades about 0.25 of its potential returns per unit of risk. Bigcommerce Holdings is currently generating about 0.43 of returns per unit of risk over similar time horizon. If you would invest 526.00 in Bigcommerce Holdings on September 2, 2024 and sell it today you would earn a total of 211.00 from holding Bigcommerce Holdings or generate 40.11% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Gitlab Inc vs. Bigcommerce Holdings
Performance |
| Timeline |
| Gitlab Inc |
| Bigcommerce Holdings |
Gitlab and Bigcommerce Holdings Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Gitlab and Bigcommerce Holdings
The main advantage of trading using opposite Gitlab and Bigcommerce Holdings positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Gitlab position performs unexpectedly, Bigcommerce Holdings 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 Bigcommerce Holdings will offset losses from the drop in Bigcommerce Holdings' long position.| Gitlab vs. Palo Alto Networks | Gitlab vs. Uipath Inc | Gitlab vs. Block Inc | Gitlab vs. Adobe Systems Incorporated |
| Bigcommerce Holdings vs. nCino Inc | Bigcommerce Holdings vs. ZoomInfo Technologies | Bigcommerce Holdings vs. Gitlab Inc | Bigcommerce Holdings vs. MondayCom |
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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