Correlation Between Ibotta and ZW Data
Can any of the company-specific risk be diversified away by investing in both Ibotta and ZW Data 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 Ibotta and ZW Data into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ibotta and ZW Data Action, you can compare the effects of market volatilities on Ibotta and ZW Data 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 Ibotta with a short position of ZW Data. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ibotta and ZW Data.
Diversification Opportunities for Ibotta and ZW Data
Poor diversification
The 3 months correlation between Ibotta and CNET is 0.6. Overlapping area represents the amount of risk that can be diversified away by holding Ibotta and ZW Data Action in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on ZW Data Action and Ibotta 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 Ibotta are associated (or correlated) with ZW Data. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of ZW Data Action has no effect on the direction of Ibotta i.e., Ibotta and ZW Data go up and down completely randomly.
Pair Corralation between Ibotta and ZW Data
Given the investment horizon of 90 days Ibotta is expected to under-perform the ZW Data. But the etf apears to be less risky and, when comparing its historical volatility, Ibotta is 1.28 times less risky than ZW Data. The etf trades about -0.15 of its potential returns per unit of risk. The ZW Data Action is currently generating about -0.09 of returns per unit of risk over similar time horizon. If you would invest 183.00 in ZW Data Action on October 30, 2025 and sell it today you would lose (60.00) from holding ZW Data Action or give up 32.79% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Ibotta vs. ZW Data Action
Performance |
| Timeline |
| Ibotta |
| ZW Data Action |
Ibotta and ZW Data Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Ibotta and ZW Data
The main advantage of trading using opposite Ibotta and ZW Data positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ibotta position performs unexpectedly, ZW Data 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 ZW Data will offset losses from the drop in ZW Data's long position.The idea behind Ibotta and ZW Data Action 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.| ZW Data vs. Baosheng Media Group | ZW Data vs. Cheetah Mobile | ZW Data vs. Onfolio Holdings | ZW Data vs. Star Fashion Culture |
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 Stock Screener module to find equities using a custom stock filter or screen asymmetry in trading patterns, price, volume, or investment outlook..
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