Correlation Between Sea and Contextlogic
Can any of the company-specific risk be diversified away by investing in both Sea and Contextlogic 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 Sea and Contextlogic into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Sea and Contextlogic, you can compare the effects of market volatilities on Sea and Contextlogic 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 Sea with a short position of Contextlogic. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sea and Contextlogic.
Diversification Opportunities for Sea and Contextlogic
0.7 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Sea and Contextlogic is 0.7. Overlapping area represents the amount of risk that can be diversified away by holding Sea and Contextlogic in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Contextlogic and Sea 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 Sea are associated (or correlated) with Contextlogic. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Contextlogic has no effect on the direction of Sea i.e., Sea and Contextlogic go up and down completely randomly.
Pair Corralation between Sea and Contextlogic
Allowing for the 90-day total investment horizon Sea is expected to generate 0.65 times more return on investment than Contextlogic. However, Sea is 1.53 times less risky than Contextlogic. It trades about 0.06 of its potential returns per unit of risk. Contextlogic is currently generating about -0.02 per unit of risk. If you would invest 6,502 in Sea on November 2, 2024 and sell it today you would earn a total of 5,843 from holding Sea or generate 89.86% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Sea vs. Contextlogic
Performance |
| Timeline |
| Sea |
| Contextlogic |
Sea and Contextlogic Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Sea and Contextlogic
The main advantage of trading using opposite Sea and Contextlogic positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sea position performs unexpectedly, Contextlogic 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 Contextlogic will offset losses from the drop in Contextlogic's long position.The idea behind Sea and Contextlogic 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.| Contextlogic vs. Keurig Dr Pepper | Contextlogic vs. Willamette Valley Vineyards | Contextlogic vs. PepsiCo | Contextlogic vs. Constellation Brands Class |
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 Competition Analyzer module to analyze and compare many basic indicators for a group of related or unrelated entities.
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