Correlation Between OSE Pharma and Dow Jones
Can any of the company-specific risk be diversified away by investing in both OSE Pharma and Dow Jones 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 OSE Pharma and Dow Jones into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between OSE Pharma SA and Dow Jones Industrial, you can compare the effects of market volatilities on OSE Pharma and Dow Jones 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 OSE Pharma with a short position of Dow Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of OSE Pharma and Dow Jones.
Diversification Opportunities for OSE Pharma and Dow Jones
0.52 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between OSE and Dow is 0.52. Overlapping area represents the amount of risk that can be diversified away by holding OSE Pharma SA and Dow Jones Industrial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dow Jones Industrial and OSE Pharma 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 OSE Pharma SA are associated (or correlated) with Dow Jones. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dow Jones Industrial has no effect on the direction of OSE Pharma i.e., OSE Pharma and Dow Jones go up and down completely randomly.
Pair Corralation between OSE Pharma and Dow Jones
Assuming the 90 days trading horizon OSE Pharma SA is expected to generate 7.15 times more return on investment than Dow Jones. However, OSE Pharma is 7.15 times more volatile than Dow Jones Industrial. It trades about 0.03 of its potential returns per unit of risk. Dow Jones Industrial is currently generating about 0.08 per unit of risk. If you would invest 655.00 in OSE Pharma SA on August 28, 2024 and sell it today you would earn a total of 241.00 from holding OSE Pharma SA or generate 36.79% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 98.21% |
| Values | Daily Returns |
OSE Pharma SA vs. Dow Jones Industrial
Performance |
| Timeline |
OSE Pharma and Dow Jones Volatility Contrast
Predicted Return Density |
| Returns |
OSE Pharma SA
Pair trading matchups for OSE Pharma
Dow Jones Industrial
Pair trading matchups for Dow Jones
Pair Trading with OSE Pharma and Dow Jones
The main advantage of trading using opposite OSE Pharma and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if OSE Pharma position performs unexpectedly, Dow Jones 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 Dow Jones will offset losses from the drop in Dow Jones' long position.| OSE Pharma vs. Biomerieux SA | OSE Pharma vs. Eurofins Scientific SE | OSE Pharma vs. Sartorius Stedim Biotech | OSE Pharma vs. SEB SA |
| Dow Jones vs. Meiwu Technology Co | Dow Jones vs. 17 Education Technology | Dow Jones vs. 51Talk Online Education | Dow Jones vs. Afya |
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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