Correlation Between Host Hotels and DALATA HOTEL
Can any of the company-specific risk be diversified away by investing in both Host Hotels and DALATA HOTEL 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 Host Hotels and DALATA HOTEL into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Host Hotels Resorts and DALATA HOTEL, you can compare the effects of market volatilities on Host Hotels and DALATA HOTEL 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 Host Hotels with a short position of DALATA HOTEL. Check out your portfolio center. Please also check ongoing floating volatility patterns of Host Hotels and DALATA HOTEL.
Diversification Opportunities for Host Hotels and DALATA HOTEL
0.51 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Host and DALATA is 0.51. Overlapping area represents the amount of risk that can be diversified away by holding Host Hotels Resorts and DALATA HOTEL in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on DALATA HOTEL and Host 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 Host Hotels Resorts are associated (or correlated) with DALATA HOTEL. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of DALATA HOTEL has no effect on the direction of Host Hotels i.e., Host Hotels and DALATA HOTEL go up and down completely randomly.
Pair Corralation between Host Hotels and DALATA HOTEL
Assuming the 90 days horizon Host Hotels is expected to generate 2.31 times less return on investment than DALATA HOTEL. But when comparing it to its historical volatility, Host Hotels Resorts is 2.06 times less risky than DALATA HOTEL. It trades about 0.01 of its potential returns per unit of risk. DALATA HOTEL is currently generating about 0.02 of returns per unit of risk over similar time horizon. If you would invest 426.00 in DALATA HOTEL on September 1, 2024 and sell it today you would lose (9.00) from holding DALATA HOTEL or give up 2.11% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Host Hotels Resorts vs. DALATA HOTEL
Performance |
| Timeline |
| Host Hotels Resorts |
| DALATA HOTEL |
Host Hotels and DALATA HOTEL Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Host Hotels and DALATA HOTEL
The main advantage of trading using opposite Host Hotels and DALATA HOTEL positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Host Hotels position performs unexpectedly, DALATA HOTEL 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 DALATA HOTEL will offset losses from the drop in DALATA HOTEL's long position.| Host Hotels vs. Park Hotels Resorts | Host Hotels vs. Pebblebrook Hotel Trust | Host Hotels vs. Sunstone Hotel Investors | Host Hotels vs. ASHFORD HOSPITTRUST |
| DALATA HOTEL vs. Fast Retailing Co | DALATA HOTEL vs. Carsales | DALATA HOTEL vs. MARKET VECTR RETAIL | DALATA HOTEL vs. RETAIL FOOD GROUP |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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