Correlation Between Lyxor UCITS and Lyxor UCITS
Can any of the company-specific risk be diversified away by investing in both Lyxor UCITS and Lyxor UCITS 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 Lyxor UCITS and Lyxor UCITS into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Lyxor UCITS iBoxx and Lyxor UCITS EuroMTS, you can compare the effects of market volatilities on Lyxor UCITS and Lyxor UCITS 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 Lyxor UCITS with a short position of Lyxor UCITS. Check out your portfolio center. Please also check ongoing floating volatility patterns of Lyxor UCITS and Lyxor UCITS.
Diversification Opportunities for Lyxor UCITS and Lyxor UCITS
0.44 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Lyxor and Lyxor is 0.44. Overlapping area represents the amount of risk that can be diversified away by holding Lyxor UCITS iBoxx and Lyxor UCITS EuroMTS in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Lyxor UCITS EuroMTS and Lyxor UCITS 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 Lyxor UCITS iBoxx are associated (or correlated) with Lyxor UCITS. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Lyxor UCITS EuroMTS has no effect on the direction of Lyxor UCITS i.e., Lyxor UCITS and Lyxor UCITS go up and down completely randomly.
Pair Corralation between Lyxor UCITS and Lyxor UCITS
Assuming the 90 days trading horizon Lyxor UCITS iBoxx is expected to generate 0.75 times more return on investment than Lyxor UCITS. However, Lyxor UCITS iBoxx is 1.34 times less risky than Lyxor UCITS. It trades about 0.13 of its potential returns per unit of risk. Lyxor UCITS EuroMTS is currently generating about 0.08 per unit of risk. If you would invest 10,642 in Lyxor UCITS iBoxx on August 29, 2024 and sell it today you would earn a total of 49.00 from holding Lyxor UCITS iBoxx or generate 0.46% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Lyxor UCITS iBoxx vs. Lyxor UCITS EuroMTS
Performance |
| Timeline |
| Lyxor UCITS iBoxx |
| Lyxor UCITS EuroMTS |
Lyxor UCITS and Lyxor UCITS Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Lyxor UCITS and Lyxor UCITS
The main advantage of trading using opposite Lyxor UCITS and Lyxor UCITS positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Lyxor UCITS position performs unexpectedly, Lyxor UCITS 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 Lyxor UCITS will offset losses from the drop in Lyxor UCITS's long position.| Lyxor UCITS vs. Lyxor SP 500 | Lyxor UCITS vs. Lyxor UCITS Daily | Lyxor UCITS vs. Lyxor UCITS MSCI | Lyxor UCITS vs. Lyxor Treasury 10Y |
| Lyxor UCITS vs. Lyxor SP 500 | Lyxor UCITS vs. Lyxor UCITS Daily | Lyxor UCITS vs. Lyxor UCITS MSCI | Lyxor UCITS vs. Lyxor Treasury 10Y |
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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