Correlation Between WHA Industrial and Quality Houses
Can any of the company-specific risk be diversified away by investing in both WHA Industrial and Quality Houses 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 WHA Industrial and Quality Houses into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between WHA Industrial Leasehold and Quality Houses Property, you can compare the effects of market volatilities on WHA Industrial and Quality Houses 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 WHA Industrial with a short position of Quality Houses. Check out your portfolio center. Please also check ongoing floating volatility patterns of WHA Industrial and Quality Houses.
Diversification Opportunities for WHA Industrial and Quality Houses
0.71 | Correlation Coefficient |
Poor diversification
The 3 months correlation between WHA and Quality is 0.71. Overlapping area represents the amount of risk that can be diversified away by holding WHA Industrial Leasehold and Quality Houses Property in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Quality Houses Property and WHA Industrial 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 WHA Industrial Leasehold are associated (or correlated) with Quality Houses. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Quality Houses Property has no effect on the direction of WHA Industrial i.e., WHA Industrial and Quality Houses go up and down completely randomly.
Pair Corralation between WHA Industrial and Quality Houses
Assuming the 90 days trading horizon WHA Industrial Leasehold is expected to generate 1.51 times more return on investment than Quality Houses. However, WHA Industrial is 1.51 times more volatile than Quality Houses Property. It trades about 0.17 of its potential returns per unit of risk. Quality Houses Property is currently generating about -0.26 per unit of risk. If you would invest 631.00 in WHA Industrial Leasehold on August 29, 2024 and sell it today you would earn a total of 29.00 from holding WHA Industrial Leasehold or generate 4.6% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
WHA Industrial Leasehold vs. Quality Houses Property
Performance |
| Timeline |
| WHA Industrial Leasehold |
| Quality Houses Property |
WHA Industrial and Quality Houses Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with WHA Industrial and Quality Houses
The main advantage of trading using opposite WHA Industrial and Quality Houses positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if WHA Industrial position performs unexpectedly, Quality Houses 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 Houses will offset losses from the drop in Quality Houses' long position.| WHA Industrial vs. Delta Electronics Public | WHA Industrial vs. Delta Electronics Public | WHA Industrial vs. Airports of Thailand | WHA Industrial vs. Airports of Thailand |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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