Correlation Between Heng Leasing and Quality Hospitality
Can any of the company-specific risk be diversified away by investing in both Heng Leasing and Quality 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 Heng Leasing and Quality Hospitality into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Heng Leasing Capital and Quality Hospitality Leasehold, you can compare the effects of market volatilities on Heng Leasing and Quality 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 Heng Leasing with a short position of Quality Hospitality. Check out your portfolio center. Please also check ongoing floating volatility patterns of Heng Leasing and Quality Hospitality.
Diversification Opportunities for Heng Leasing and Quality Hospitality
-0.37 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Heng and Quality is -0.37. Overlapping area represents the amount of risk that can be diversified away by holding Heng Leasing Capital and Quality Hospitality Leasehold in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Quality Hospitality and Heng Leasing 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 Heng Leasing Capital are associated (or correlated) with Quality Hospitality. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Quality Hospitality has no effect on the direction of Heng Leasing i.e., Heng Leasing and Quality Hospitality go up and down completely randomly.
Pair Corralation between Heng Leasing and Quality Hospitality
Assuming the 90 days trading horizon Heng Leasing Capital is expected to generate 0.97 times more return on investment than Quality Hospitality. However, Heng Leasing Capital is 1.03 times less risky than Quality Hospitality. It trades about 0.02 of its potential returns per unit of risk. Quality Hospitality Leasehold is currently generating about -0.03 per unit of risk. If you would invest 106.00 in Heng Leasing Capital on December 23, 2024 and sell it today you would earn a total of 1.00 from holding Heng Leasing Capital or generate 0.94% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 98.41% |
Values | Daily Returns |
Heng Leasing Capital vs. Quality Hospitality Leasehold
Performance |
Timeline |
Heng Leasing Capital |
Quality Hospitality |
Heng Leasing and Quality Hospitality Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Heng Leasing and Quality Hospitality
The main advantage of trading using opposite Heng Leasing and Quality Hospitality positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Heng Leasing position performs unexpectedly, Quality 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 Quality Hospitality will offset losses from the drop in Quality Hospitality's long position.Heng Leasing vs. Bangkok Commercial Asset | Heng Leasing vs. Siam Global House | Heng Leasing vs. Dohome Public | Heng Leasing vs. JMT Network 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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.
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