Correlation Between Xenia Hotels and China Oilfield
Can any of the company-specific risk be diversified away by investing in both Xenia Hotels and China Oilfield 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 Xenia Hotels and China Oilfield into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Xenia Hotels Resorts and China Oilfield Services, you can compare the effects of market volatilities on Xenia Hotels and China Oilfield 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 Xenia Hotels with a short position of China Oilfield. Check out your portfolio center. Please also check ongoing floating volatility patterns of Xenia Hotels and China Oilfield.
Diversification Opportunities for Xenia Hotels and China Oilfield
-0.69 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Xenia and China is -0.69. Overlapping area represents the amount of risk that can be diversified away by holding Xenia Hotels Resorts and China Oilfield Services in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on China Oilfield Services and Xenia 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 Xenia Hotels Resorts are associated (or correlated) with China Oilfield. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of China Oilfield Services has no effect on the direction of Xenia Hotels i.e., Xenia Hotels and China Oilfield go up and down completely randomly.
Pair Corralation between Xenia Hotels and China Oilfield
Assuming the 90 days trading horizon Xenia Hotels is expected to generate 2.68 times less return on investment than China Oilfield. But when comparing it to its historical volatility, Xenia Hotels Resorts is 1.78 times less risky than China Oilfield. It trades about 0.02 of its potential returns per unit of risk. China Oilfield Services is currently generating about 0.03 of returns per unit of risk over similar time horizon. If you would invest 64.00 in China Oilfield Services on October 13, 2024 and sell it today you would earn a total of 22.00 from holding China Oilfield Services or generate 34.38% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Xenia Hotels Resorts vs. China Oilfield Services
Performance |
Timeline |
Xenia Hotels Resorts |
China Oilfield Services |
Xenia Hotels and China Oilfield Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Xenia Hotels and China Oilfield
The main advantage of trading using opposite Xenia Hotels and China Oilfield positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Xenia Hotels position performs unexpectedly, China Oilfield 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 China Oilfield will offset losses from the drop in China Oilfield's long position.Xenia Hotels vs. DALATA HOTEL | Xenia Hotels vs. SILVER BULLET DATA | Xenia Hotels vs. Northern Data AG | Xenia Hotels vs. Pure Storage |
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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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