Correlation Between Datasonic Group and YTL Hospitality
Can any of the company-specific risk be diversified away by investing in both Datasonic Group and YTL 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 Datasonic Group and YTL Hospitality into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Datasonic Group Bhd and YTL Hospitality REIT, you can compare the effects of market volatilities on Datasonic Group and YTL 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 Datasonic Group with a short position of YTL Hospitality. Check out your portfolio center. Please also check ongoing floating volatility patterns of Datasonic Group and YTL Hospitality.
Diversification Opportunities for Datasonic Group and YTL Hospitality
0.38 | Correlation Coefficient |
Weak diversification
The 3 months correlation between Datasonic and YTL is 0.38. Overlapping area represents the amount of risk that can be diversified away by holding Datasonic Group Bhd and YTL Hospitality REIT in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on YTL Hospitality REIT and Datasonic Group 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 Datasonic Group Bhd are associated (or correlated) with YTL Hospitality. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of YTL Hospitality REIT has no effect on the direction of Datasonic Group i.e., Datasonic Group and YTL Hospitality go up and down completely randomly.
Pair Corralation between Datasonic Group and YTL Hospitality
Assuming the 90 days trading horizon Datasonic Group Bhd is expected to under-perform the YTL Hospitality. In addition to that, Datasonic Group is 2.39 times more volatile than YTL Hospitality REIT. It trades about -0.04 of its total potential returns per unit of risk. YTL Hospitality REIT is currently generating about -0.04 per unit of volatility. If you would invest 122.00 in YTL Hospitality REIT on September 27, 2024 and sell it today you would lose (3.00) from holding YTL Hospitality REIT or give up 2.46% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Datasonic Group Bhd vs. YTL Hospitality REIT
Performance |
Timeline |
Datasonic Group Bhd |
YTL Hospitality REIT |
Datasonic Group and YTL Hospitality Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Datasonic Group and YTL Hospitality
The main advantage of trading using opposite Datasonic Group and YTL Hospitality positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Datasonic Group position performs unexpectedly, YTL 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 YTL Hospitality will offset losses from the drop in YTL Hospitality's long position.Datasonic Group vs. Dagang Nexchange Bhd | Datasonic Group vs. Awanbiru Technology Bhd | Datasonic Group vs. Dataprep Holdings Bhd | Datasonic Group vs. TechnoDex Bhd |
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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 Portfolio Rebalancing module to analyze risk-adjusted returns against different time horizons to find asset-allocation targets.
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