Correlation Between Berli Jucker and Chularat Hospital
Can any of the company-specific risk be diversified away by investing in both Berli Jucker and Chularat Hospital 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 Berli Jucker and Chularat Hospital into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Berli Jucker Public and Chularat Hospital Public, you can compare the effects of market volatilities on Berli Jucker and Chularat Hospital 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 Berli Jucker with a short position of Chularat Hospital. Check out your portfolio center. Please also check ongoing floating volatility patterns of Berli Jucker and Chularat Hospital.
Diversification Opportunities for Berli Jucker and Chularat Hospital
0.89 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Berli and Chularat is 0.89. Overlapping area represents the amount of risk that can be diversified away by holding Berli Jucker Public and Chularat Hospital Public in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Chularat Hospital Public and Berli Jucker 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 Berli Jucker Public are associated (or correlated) with Chularat Hospital. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Chularat Hospital Public has no effect on the direction of Berli Jucker i.e., Berli Jucker and Chularat Hospital go up and down completely randomly.
Pair Corralation between Berli Jucker and Chularat Hospital
Assuming the 90 days trading horizon Berli Jucker Public is expected to generate 0.74 times more return on investment than Chularat Hospital. However, Berli Jucker Public is 1.35 times less risky than Chularat Hospital. It trades about -0.09 of its potential returns per unit of risk. Chularat Hospital Public is currently generating about -0.14 per unit of risk. If you would invest 2,410 in Berli Jucker Public on December 1, 2024 and sell it today you would lose (220.00) from holding Berli Jucker Public or give up 9.13% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Berli Jucker Public vs. Chularat Hospital Public
Performance |
Timeline |
Berli Jucker Public |
Chularat Hospital Public |
Berli Jucker and Chularat Hospital Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Berli Jucker and Chularat Hospital
The main advantage of trading using opposite Berli Jucker and Chularat Hospital positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Berli Jucker position performs unexpectedly, Chularat Hospital 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 Chularat Hospital will offset losses from the drop in Chularat Hospital's long position.Berli Jucker vs. CP ALL Public | Berli Jucker vs. Bangkok Dusit Medical | Berli Jucker vs. BTS Group Holdings | Berli Jucker vs. Central Pattana Public |
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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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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