Correlation Between Arinsiri Land and Singha Estate
Can any of the company-specific risk be diversified away by investing in both Arinsiri Land and Singha Estate 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 Arinsiri Land and Singha Estate into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Arinsiri Land Public and Singha Estate Public, you can compare the effects of market volatilities on Arinsiri Land and Singha Estate 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 Arinsiri Land with a short position of Singha Estate. Check out your portfolio center. Please also check ongoing floating volatility patterns of Arinsiri Land and Singha Estate.
Diversification Opportunities for Arinsiri Land and Singha Estate
0.52 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Arinsiri and Singha is 0.52. Overlapping area represents the amount of risk that can be diversified away by holding Arinsiri Land Public and Singha Estate Public in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Singha Estate Public and Arinsiri Land 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 Arinsiri Land Public are associated (or correlated) with Singha Estate. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Singha Estate Public has no effect on the direction of Arinsiri Land i.e., Arinsiri Land and Singha Estate go up and down completely randomly.
Pair Corralation between Arinsiri Land and Singha Estate
Assuming the 90 days trading horizon Arinsiri Land Public is expected to under-perform the Singha Estate. But the stock apears to be less risky and, when comparing its historical volatility, Arinsiri Land Public is 25.51 times less risky than Singha Estate. The stock trades about -0.19 of its potential returns per unit of risk. The Singha Estate Public is currently generating about 0.11 of returns per unit of risk over similar time horizon. If you would invest 131.00 in Singha Estate Public on September 26, 2024 and sell it today you would lose (40.00) from holding Singha Estate Public or give up 30.53% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 98.36% |
Values | Daily Returns |
Arinsiri Land Public vs. Singha Estate Public
Performance |
Timeline |
Arinsiri Land Public |
Singha Estate Public |
Arinsiri Land and Singha Estate Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Arinsiri Land and Singha Estate
The main advantage of trading using opposite Arinsiri Land and Singha Estate positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Arinsiri Land position performs unexpectedly, Singha Estate 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 Singha Estate will offset losses from the drop in Singha Estate's long position.Arinsiri Land vs. Frasers Property Public | Arinsiri Land vs. Singha Estate Public | Arinsiri Land vs. Areeya Property Public | Arinsiri Land vs. Asset Five Group |
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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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