Correlation Between MOBILE FACTORY and PPHE HOTEL
Can any of the company-specific risk be diversified away by investing in both MOBILE FACTORY and PPHE 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 MOBILE FACTORY and PPHE HOTEL into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between MOBILE FACTORY INC and PPHE HOTEL GROUP, you can compare the effects of market volatilities on MOBILE FACTORY and PPHE 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 MOBILE FACTORY with a short position of PPHE HOTEL. Check out your portfolio center. Please also check ongoing floating volatility patterns of MOBILE FACTORY and PPHE HOTEL.
Diversification Opportunities for MOBILE FACTORY and PPHE HOTEL
0.42 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between MOBILE and PPHE is 0.42. Overlapping area represents the amount of risk that can be diversified away by holding MOBILE FACTORY INC and PPHE HOTEL GROUP in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on PPHE HOTEL GROUP and MOBILE FACTORY 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 MOBILE FACTORY INC are associated (or correlated) with PPHE HOTEL. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of PPHE HOTEL GROUP has no effect on the direction of MOBILE FACTORY i.e., MOBILE FACTORY and PPHE HOTEL go up and down completely randomly.
Pair Corralation between MOBILE FACTORY and PPHE HOTEL
Assuming the 90 days horizon MOBILE FACTORY is expected to generate 14.49 times less return on investment than PPHE HOTEL. In addition to that, MOBILE FACTORY is 1.22 times more volatile than PPHE HOTEL GROUP. It trades about 0.0 of its total potential returns per unit of risk. PPHE HOTEL GROUP is currently generating about 0.04 per unit of volatility. If you would invest 1,222 in PPHE HOTEL GROUP on October 11, 2024 and sell it today you would earn a total of 368.00 from holding PPHE HOTEL GROUP or generate 30.11% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
MOBILE FACTORY INC vs. PPHE HOTEL GROUP
Performance |
| Timeline |
| MOBILE FACTORY INC |
| PPHE HOTEL GROUP |
MOBILE FACTORY and PPHE HOTEL Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with MOBILE FACTORY and PPHE HOTEL
The main advantage of trading using opposite MOBILE FACTORY and PPHE HOTEL positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if MOBILE FACTORY position performs unexpectedly, PPHE 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 PPHE HOTEL will offset losses from the drop in PPHE HOTEL's long position.| MOBILE FACTORY vs. Constellation Software | MOBILE FACTORY vs. Easy Software AG | MOBILE FACTORY vs. CPU SOFTWAREHOUSE | MOBILE FACTORY vs. Kingdee International Software |
| PPHE HOTEL vs. T MOBILE US | PPHE HOTEL vs. Cogent Communications Holdings | PPHE HOTEL vs. MOBILE FACTORY INC | PPHE HOTEL vs. Air Transport Services |
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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