Correlation Between Europlasma and Innate Pharma
Can any of the company-specific risk be diversified away by investing in both Europlasma and Innate Pharma 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 Europlasma and Innate Pharma into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Europlasma SA and Innate Pharma, you can compare the effects of market volatilities on Europlasma and Innate Pharma 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 Europlasma with a short position of Innate Pharma. Check out your portfolio center. Please also check ongoing floating volatility patterns of Europlasma and Innate Pharma.
Diversification Opportunities for Europlasma and Innate Pharma
0.89 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Europlasma and Innate is 0.89. Overlapping area represents the amount of risk that can be diversified away by holding Europlasma SA and Innate Pharma in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Innate Pharma and Europlasma 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 Europlasma SA are associated (or correlated) with Innate Pharma. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Innate Pharma has no effect on the direction of Europlasma i.e., Europlasma and Innate Pharma go up and down completely randomly.
Pair Corralation between Europlasma and Innate Pharma
Assuming the 90 days trading horizon Europlasma SA is expected to generate 8.31 times more return on investment than Innate Pharma. However, Europlasma is 8.31 times more volatile than Innate Pharma. It trades about 0.01 of its potential returns per unit of risk. Innate Pharma is currently generating about -0.25 per unit of risk. If you would invest 20.00 in Europlasma SA on September 2, 2024 and sell it today you would lose (10.50) from holding Europlasma SA or give up 52.5% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Europlasma SA vs. Innate Pharma
Performance |
Timeline |
Europlasma SA |
Innate Pharma |
Europlasma and Innate Pharma Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Europlasma and Innate Pharma
The main advantage of trading using opposite Europlasma and Innate Pharma positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Europlasma position performs unexpectedly, Innate Pharma 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 Innate Pharma will offset losses from the drop in Innate Pharma's long position.The idea behind Europlasma SA and Innate Pharma 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.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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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