Correlation Between Meliá Hotels and COMMERCIAL VEHICLE
Can any of the company-specific risk be diversified away by investing in both Meliá Hotels and COMMERCIAL VEHICLE 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 Meliá Hotels and COMMERCIAL VEHICLE into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Meli Hotels International and COMMERCIAL VEHICLE, you can compare the effects of market volatilities on Meliá Hotels and COMMERCIAL VEHICLE 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 Meliá Hotels with a short position of COMMERCIAL VEHICLE. Check out your portfolio center. Please also check ongoing floating volatility patterns of Meliá Hotels and COMMERCIAL VEHICLE.
Diversification Opportunities for Meliá Hotels and COMMERCIAL VEHICLE
-0.7 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Meliá and COMMERCIAL is -0.7. Overlapping area represents the amount of risk that can be diversified away by holding Meli Hotels International and COMMERCIAL VEHICLE in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on COMMERCIAL VEHICLE and Meliá Hotels 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 Meli Hotels International are associated (or correlated) with COMMERCIAL VEHICLE. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of COMMERCIAL VEHICLE has no effect on the direction of Meliá Hotels i.e., Meliá Hotels and COMMERCIAL VEHICLE go up and down completely randomly.
Pair Corralation between Meliá Hotels and COMMERCIAL VEHICLE
Assuming the 90 days horizon Meli Hotels International is expected to generate 0.52 times more return on investment than COMMERCIAL VEHICLE. However, Meli Hotels International is 1.92 times less risky than COMMERCIAL VEHICLE. It trades about 0.03 of its potential returns per unit of risk. COMMERCIAL VEHICLE is currently generating about -0.06 per unit of risk. If you would invest 596.00 in Meli Hotels International on October 15, 2024 and sell it today you would earn a total of 120.00 from holding Meli Hotels International or generate 20.13% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Meli Hotels International vs. COMMERCIAL VEHICLE
Performance |
Timeline |
Meli Hotels International |
COMMERCIAL VEHICLE |
Meliá Hotels and COMMERCIAL VEHICLE Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Meliá Hotels and COMMERCIAL VEHICLE
The main advantage of trading using opposite Meliá Hotels and COMMERCIAL VEHICLE positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Meliá Hotels position performs unexpectedly, COMMERCIAL VEHICLE 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 COMMERCIAL VEHICLE will offset losses from the drop in COMMERCIAL VEHICLE's long position.Meliá Hotels vs. Yuexiu Transport Infrastructure | Meliá Hotels vs. SEI INVESTMENTS | Meliá Hotels vs. Aluminum of | Meliá Hotels vs. SWISS WATER DECAFFCOFFEE |
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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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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