Correlation Between Shangri La and Surapon Foods
Can any of the company-specific risk be diversified away by investing in both Shangri La and Surapon Foods 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 Shangri La and Surapon Foods into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Shangri La Hotel Public and Surapon Foods Public, you can compare the effects of market volatilities on Shangri La and Surapon Foods 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 Shangri La with a short position of Surapon Foods. Check out your portfolio center. Please also check ongoing floating volatility patterns of Shangri La and Surapon Foods.
Diversification Opportunities for Shangri La and Surapon Foods
0.03 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Shangri and Surapon is 0.03. Overlapping area represents the amount of risk that can be diversified away by holding Shangri La Hotel Public and Surapon Foods Public in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Surapon Foods Public and Shangri La 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 Shangri La Hotel Public are associated (or correlated) with Surapon Foods. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Surapon Foods Public has no effect on the direction of Shangri La i.e., Shangri La and Surapon Foods go up and down completely randomly.
Pair Corralation between Shangri La and Surapon Foods
Assuming the 90 days trading horizon Shangri La Hotel Public is expected to under-perform the Surapon Foods. But the stock apears to be less risky and, when comparing its historical volatility, Shangri La Hotel Public is 1.58 times less risky than Surapon Foods. The stock trades about -0.28 of its potential returns per unit of risk. The Surapon Foods Public is currently generating about -0.04 of returns per unit of risk over similar time horizon. If you would invest 695.00 in Surapon Foods Public on September 13, 2024 and sell it today you would lose (10.00) from holding Surapon Foods Public or give up 1.44% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Shangri La Hotel Public vs. Surapon Foods Public
Performance |
| Timeline |
| Shangri La Hotel |
| Surapon Foods Public |
Shangri La and Surapon Foods Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Shangri La and Surapon Foods
The main advantage of trading using opposite Shangri La and Surapon Foods positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Shangri La position performs unexpectedly, Surapon Foods 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 Surapon Foods will offset losses from the drop in Surapon Foods' long position.| Shangri La vs. Advanced Information Technology | Shangri La vs. BPS TECHNOLOGY PUBLIC | Shangri La vs. Dexon Technology PCL | Shangri La vs. Silicon Craft Technology |
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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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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