Correlation Between Amphastar and EssilorLuxottica
Can any of the company-specific risk be diversified away by investing in both Amphastar and EssilorLuxottica 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 Amphastar and EssilorLuxottica into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Amphastar P and EssilorLuxottica Socit anonyme, you can compare the effects of market volatilities on Amphastar and EssilorLuxottica 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 Amphastar with a short position of EssilorLuxottica. Check out your portfolio center. Please also check ongoing floating volatility patterns of Amphastar and EssilorLuxottica.
Diversification Opportunities for Amphastar and EssilorLuxottica
-0.46 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Amphastar and EssilorLuxottica is -0.46. Overlapping area represents the amount of risk that can be diversified away by holding Amphastar P and EssilorLuxottica Socit anonyme in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on EssilorLuxottica Socit and Amphastar 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 Amphastar P are associated (or correlated) with EssilorLuxottica. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of EssilorLuxottica Socit has no effect on the direction of Amphastar i.e., Amphastar and EssilorLuxottica go up and down completely randomly.
Pair Corralation between Amphastar and EssilorLuxottica
Given the investment horizon of 90 days Amphastar P is expected to under-perform the EssilorLuxottica. In addition to that, Amphastar is 1.37 times more volatile than EssilorLuxottica Socit anonyme. It trades about -0.09 of its total potential returns per unit of risk. EssilorLuxottica Socit anonyme is currently generating about 0.1 per unit of volatility. If you would invest 23,448 in EssilorLuxottica Socit anonyme on November 2, 2024 and sell it today you would earn a total of 4,192 from holding EssilorLuxottica Socit anonyme or generate 17.88% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Amphastar P vs. EssilorLuxottica Socit anonyme
Performance |
| Timeline |
| Amphastar P |
| EssilorLuxottica Socit |
Amphastar and EssilorLuxottica Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Amphastar and EssilorLuxottica
The main advantage of trading using opposite Amphastar and EssilorLuxottica positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Amphastar position performs unexpectedly, EssilorLuxottica 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 EssilorLuxottica will offset losses from the drop in EssilorLuxottica's long position.| Amphastar vs. Collegium Pharmaceutical | Amphastar vs. Alkermes Plc | Amphastar vs. Evolus Inc | Amphastar vs. Neurocrine Biosciences |
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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 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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