Correlation Between Catalyst Biosciences and Applied Molecular
Can any of the company-specific risk be diversified away by investing in both Catalyst Biosciences and Applied Molecular 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 Catalyst Biosciences and Applied Molecular into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Catalyst Biosciences and Applied Molecular Transport, you can compare the effects of market volatilities on Catalyst Biosciences and Applied Molecular 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 Catalyst Biosciences with a short position of Applied Molecular. Check out your portfolio center. Please also check ongoing floating volatility patterns of Catalyst Biosciences and Applied Molecular.
Diversification Opportunities for Catalyst Biosciences and Applied Molecular
0.43 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Catalyst and Applied is 0.43. Overlapping area represents the amount of risk that can be diversified away by holding Catalyst Biosciences and Applied Molecular Transport in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Applied Molecular and Catalyst Biosciences 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 Catalyst Biosciences are associated (or correlated) with Applied Molecular. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Applied Molecular has no effect on the direction of Catalyst Biosciences i.e., Catalyst Biosciences and Applied Molecular go up and down completely randomly.
Pair Corralation between Catalyst Biosciences and Applied Molecular
If you would invest 33.00 in Applied Molecular Transport on October 22, 2024 and sell it today you would earn a total of 0.00 from holding Applied Molecular Transport or generate 0.0% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Catalyst Biosciences vs. Applied Molecular Transport
Performance |
| Timeline |
| Catalyst Biosciences |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
| Applied Molecular |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
Catalyst Biosciences and Applied Molecular Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Catalyst Biosciences and Applied Molecular
The main advantage of trading using opposite Catalyst Biosciences and Applied Molecular positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Catalyst Biosciences position performs unexpectedly, Applied Molecular 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 Applied Molecular will offset losses from the drop in Applied Molecular's long position.| Catalyst Biosciences vs. Akari Therapeutics PLC | Catalyst Biosciences vs. Benitec Biopharma Ltd | Catalyst Biosciences vs. Pulmatrix |
| Applied Molecular vs. Bio Path Holdings | Applied Molecular vs. Benitec Biopharma Ltd | Applied Molecular vs. Aerovate Therapeutics | Applied Molecular vs. Adagene |
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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