Correlation Between Apple and Diamondrock Hospitality
Can any of the company-specific risk be diversified away by investing in both Apple and Diamondrock Hospitality 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 Apple and Diamondrock Hospitality into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Apple Inc and Diamondrock Hospitality Co, you can compare the effects of market volatilities on Apple and Diamondrock Hospitality 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 Apple with a short position of Diamondrock Hospitality. Check out your portfolio center. Please also check ongoing floating volatility patterns of Apple and Diamondrock Hospitality.
Diversification Opportunities for Apple and Diamondrock Hospitality
0.88 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Apple and Diamondrock is 0.88. Overlapping area represents the amount of risk that can be diversified away by holding Apple Inc and Diamondrock Hospitality Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Diamondrock Hospitality and Apple 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 Apple Inc are associated (or correlated) with Diamondrock Hospitality. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Diamondrock Hospitality has no effect on the direction of Apple i.e., Apple and Diamondrock Hospitality go up and down completely randomly.
Pair Corralation between Apple and Diamondrock Hospitality
Assuming the 90 days trading horizon Apple is expected to generate 1.25 times less return on investment than Diamondrock Hospitality. But when comparing it to its historical volatility, Apple Inc is 1.48 times less risky than Diamondrock Hospitality. It trades about 0.19 of its potential returns per unit of risk. Diamondrock Hospitality Co is currently generating about 0.16 of returns per unit of risk over similar time horizon. If you would invest 757.00 in Diamondrock Hospitality Co on September 12, 2024 and sell it today you would earn a total of 158.00 from holding Diamondrock Hospitality Co or generate 20.87% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Apple Inc vs. Diamondrock Hospitality Co
Performance |
Timeline |
Apple Inc |
Diamondrock Hospitality |
Apple and Diamondrock Hospitality Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Apple and Diamondrock Hospitality
The main advantage of trading using opposite Apple and Diamondrock Hospitality positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Apple position performs unexpectedly, Diamondrock Hospitality 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 Diamondrock Hospitality will offset losses from the drop in Diamondrock Hospitality's long position.Apple vs. ON SEMICONDUCTOR | Apple vs. Burlington Stores | Apple vs. National Retail Properties | Apple vs. Goosehead Insurance |
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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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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