Correlation Between Park Hotels and City Office
Can any of the company-specific risk be diversified away by investing in both Park Hotels and City Office 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 Park Hotels and City Office into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Park Hotels Resorts and City Office, you can compare the effects of market volatilities on Park Hotels and City Office 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 Park Hotels with a short position of City Office. Check out your portfolio center. Please also check ongoing floating volatility patterns of Park Hotels and City Office.
Diversification Opportunities for Park Hotels and City Office
0.22 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Park and City is 0.22. Overlapping area represents the amount of risk that can be diversified away by holding Park Hotels Resorts and City Office in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on City Office and Park 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 Park Hotels Resorts are associated (or correlated) with City Office. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of City Office has no effect on the direction of Park Hotels i.e., Park Hotels and City Office go up and down completely randomly.
Pair Corralation between Park Hotels and City Office
Allowing for the 90-day total investment horizon Park Hotels Resorts is expected to generate 0.72 times more return on investment than City Office. However, Park Hotels Resorts is 1.39 times less risky than City Office. It trades about 0.06 of its potential returns per unit of risk. City Office is currently generating about -0.03 per unit of risk. If you would invest 1,411 in Park Hotels Resorts on October 1, 2024 and sell it today you would earn a total of 81.00 from holding Park Hotels Resorts or generate 5.74% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Park Hotels Resorts vs. City Office
Performance |
Timeline |
Park Hotels Resorts |
City Office |
Park Hotels and City Office Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Park Hotels and City Office
The main advantage of trading using opposite Park Hotels and City Office positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Park Hotels position performs unexpectedly, City Office 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 City Office will offset losses from the drop in City Office's long position.Park Hotels vs. Diamondrock Hospitality | Park Hotels vs. Ryman Hospitality Properties | Park Hotels vs. Sunstone Hotel Investors | Park Hotels vs. Summit Hotel Properties |
City Office vs. Hudson Pacific Properties | City Office vs. Piedmont Office Realty | City Office vs. Office Properties Income | City Office vs. Kilroy Realty Corp |
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 Volatility Analysis module to get historical volatility and risk analysis based on latest market data.
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