Correlation Between NYSE Composite and LVMH Moet
Can any of the company-specific risk be diversified away by investing in both NYSE Composite and LVMH Moet 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 NYSE Composite and LVMH Moet into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between NYSE Composite and LVMH Moet Hennessy, you can compare the effects of market volatilities on NYSE Composite and LVMH Moet 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 NYSE Composite with a short position of LVMH Moet. Check out your portfolio center. Please also check ongoing floating volatility patterns of NYSE Composite and LVMH Moet.
Diversification Opportunities for NYSE Composite and LVMH Moet
0.42 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between NYSE and LVMH is 0.42. Overlapping area represents the amount of risk that can be diversified away by holding NYSE Composite and LVMH Moet Hennessy in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on LVMH Moet Hennessy and NYSE Composite 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 NYSE Composite are associated (or correlated) with LVMH Moet. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of LVMH Moet Hennessy has no effect on the direction of NYSE Composite i.e., NYSE Composite and LVMH Moet go up and down completely randomly.
Pair Corralation between NYSE Composite and LVMH Moet
Assuming the 90 days trading horizon NYSE Composite is expected to generate 5.75 times less return on investment than LVMH Moet. But when comparing it to its historical volatility, NYSE Composite is 2.29 times less risky than LVMH Moet. It trades about 0.08 of its potential returns per unit of risk. LVMH Moet Hennessy is currently generating about 0.2 of returns per unit of risk over similar time horizon. If you would invest 14,911 in LVMH Moet Hennessy on August 27, 2024 and sell it today you would earn a total of 2,284 from holding LVMH Moet Hennessy or generate 15.32% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 9.07% |
Values | Daily Returns |
NYSE Composite vs. LVMH Moet Hennessy
Performance |
Timeline |
NYSE Composite and LVMH Moet Volatility Contrast
Predicted Return Density |
Returns |
NYSE Composite
Pair trading matchups for NYSE Composite
LVMH Moet Hennessy
Pair trading matchups for LVMH Moet
Pair Trading with NYSE Composite and LVMH Moet
The main advantage of trading using opposite NYSE Composite and LVMH Moet positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if NYSE Composite position performs unexpectedly, LVMH Moet 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 LVMH Moet will offset losses from the drop in LVMH Moet's long position.NYSE Composite vs. Hooker Furniture | NYSE Composite vs. Hudson Pacific Properties | NYSE Composite vs. Canlan Ice Sports | NYSE Composite vs. Boston Properties |
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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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