Correlation Between Valneva SE and Catalyst Pharmaceuticals
Can any of the company-specific risk be diversified away by investing in both Valneva SE and Catalyst Pharmaceuticals 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 Valneva SE and Catalyst Pharmaceuticals into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Valneva SE ADR and Catalyst Pharmaceuticals, you can compare the effects of market volatilities on Valneva SE and Catalyst Pharmaceuticals 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 Valneva SE with a short position of Catalyst Pharmaceuticals. Check out your portfolio center. Please also check ongoing floating volatility patterns of Valneva SE and Catalyst Pharmaceuticals.
Diversification Opportunities for Valneva SE and Catalyst Pharmaceuticals
-0.54 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Valneva and Catalyst is -0.54. Overlapping area represents the amount of risk that can be diversified away by holding Valneva SE ADR and Catalyst Pharmaceuticals in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Catalyst Pharmaceuticals and Valneva SE 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 Valneva SE ADR are associated (or correlated) with Catalyst Pharmaceuticals. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Catalyst Pharmaceuticals has no effect on the direction of Valneva SE i.e., Valneva SE and Catalyst Pharmaceuticals go up and down completely randomly.
Pair Corralation between Valneva SE and Catalyst Pharmaceuticals
Given the investment horizon of 90 days Valneva SE ADR is expected to under-perform the Catalyst Pharmaceuticals. In addition to that, Valneva SE is 1.42 times more volatile than Catalyst Pharmaceuticals. It trades about -0.08 of its total potential returns per unit of risk. Catalyst Pharmaceuticals is currently generating about 0.09 per unit of volatility. If you would invest 1,443 in Catalyst Pharmaceuticals on August 29, 2024 and sell it today you would earn a total of 750.00 from holding Catalyst Pharmaceuticals or generate 51.98% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Valneva SE ADR vs. Catalyst Pharmaceuticals
Performance |
| Timeline |
| Valneva SE ADR |
| Catalyst Pharmaceuticals |
Valneva SE and Catalyst Pharmaceuticals Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Valneva SE and Catalyst Pharmaceuticals
The main advantage of trading using opposite Valneva SE and Catalyst Pharmaceuticals positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Valneva SE position performs unexpectedly, Catalyst Pharmaceuticals 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 Catalyst Pharmaceuticals will offset losses from the drop in Catalyst Pharmaceuticals' long position.| Valneva SE vs. Bright Minds Biosciences | Valneva SE vs. HP Inc | Valneva SE vs. Intel | Valneva SE vs. Chevron Corp |
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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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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