Correlation Between MediciNova and Foghorn Therapeutics
Can any of the company-specific risk be diversified away by investing in both MediciNova and Foghorn Therapeutics 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 MediciNova and Foghorn Therapeutics into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between MediciNova and Foghorn Therapeutics, you can compare the effects of market volatilities on MediciNova and Foghorn Therapeutics 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 MediciNova with a short position of Foghorn Therapeutics. Check out your portfolio center. Please also check ongoing floating volatility patterns of MediciNova and Foghorn Therapeutics.
Diversification Opportunities for MediciNova and Foghorn Therapeutics
0.03 | Correlation Coefficient |
Significant diversification
The 3 months correlation between MediciNova and Foghorn is 0.03. Overlapping area represents the amount of risk that can be diversified away by holding MediciNova and Foghorn Therapeutics in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Foghorn Therapeutics and MediciNova 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 MediciNova are associated (or correlated) with Foghorn Therapeutics. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Foghorn Therapeutics has no effect on the direction of MediciNova i.e., MediciNova and Foghorn Therapeutics go up and down completely randomly.
Pair Corralation between MediciNova and Foghorn Therapeutics
Given the investment horizon of 90 days MediciNova is expected to generate 2.82 times more return on investment than Foghorn Therapeutics. However, MediciNova is 2.82 times more volatile than Foghorn Therapeutics. It trades about 0.14 of its potential returns per unit of risk. Foghorn Therapeutics is currently generating about -0.06 per unit of risk. If you would invest 163.00 in MediciNova on August 28, 2024 and sell it today you would earn a total of 45.00 from holding MediciNova or generate 27.61% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
MediciNova vs. Foghorn Therapeutics
Performance |
Timeline |
MediciNova |
Foghorn Therapeutics |
MediciNova and Foghorn Therapeutics Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with MediciNova and Foghorn Therapeutics
The main advantage of trading using opposite MediciNova and Foghorn Therapeutics positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if MediciNova position performs unexpectedly, Foghorn Therapeutics 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 Foghorn Therapeutics will offset losses from the drop in Foghorn Therapeutics' long position.MediciNova vs. Eliem Therapeutics | MediciNova vs. Scpharmaceuticals | MediciNova vs. Milestone Pharmaceuticals | MediciNova vs. Seres Therapeutics |
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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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.
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