Correlation Between Muang Thai and CENTRAL RETAIL
Can any of the company-specific risk be diversified away by investing in both Muang Thai and CENTRAL RETAIL 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 Muang Thai and CENTRAL RETAIL into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Muang Thai Insurance and CENTRAL RETAIL P, you can compare the effects of market volatilities on Muang Thai and CENTRAL RETAIL 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 Muang Thai with a short position of CENTRAL RETAIL. Check out your portfolio center. Please also check ongoing floating volatility patterns of Muang Thai and CENTRAL RETAIL.
Diversification Opportunities for Muang Thai and CENTRAL RETAIL
0.14 | Correlation Coefficient |
Average diversification
The 3 months correlation between Muang and CENTRAL is 0.14. Overlapping area represents the amount of risk that can be diversified away by holding Muang Thai Insurance and CENTRAL RETAIL P in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CENTRAL RETAIL P and Muang Thai 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 Muang Thai Insurance are associated (or correlated) with CENTRAL RETAIL. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CENTRAL RETAIL P has no effect on the direction of Muang Thai i.e., Muang Thai and CENTRAL RETAIL go up and down completely randomly.
Pair Corralation between Muang Thai and CENTRAL RETAIL
Assuming the 90 days trading horizon Muang Thai Insurance is expected to generate 59.82 times more return on investment than CENTRAL RETAIL. However, Muang Thai is 59.82 times more volatile than CENTRAL RETAIL P. It trades about 0.04 of its potential returns per unit of risk. CENTRAL RETAIL P is currently generating about -0.05 per unit of risk. If you would invest 11,276 in Muang Thai Insurance on October 8, 2024 and sell it today you would lose (776.00) from holding Muang Thai Insurance or give up 6.88% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Muang Thai Insurance vs. CENTRAL RETAIL P
Performance |
Timeline |
Muang Thai Insurance |
CENTRAL RETAIL P |
Muang Thai and CENTRAL RETAIL Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Muang Thai and CENTRAL RETAIL
The main advantage of trading using opposite Muang Thai and CENTRAL RETAIL positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Muang Thai position performs unexpectedly, CENTRAL RETAIL 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 CENTRAL RETAIL will offset losses from the drop in CENTRAL RETAIL's long position.Muang Thai vs. Bangkok Life Assurance | Muang Thai vs. Karmarts Public | Muang Thai vs. Kang Yong Electric | Muang Thai vs. Kiatnakin Phatra Bank |
CENTRAL RETAIL vs. Earth Tech Environment | CENTRAL RETAIL vs. CHAOSUA FOODS INDUSTRY | CENTRAL RETAIL vs. Charan Insurance Public | CENTRAL RETAIL vs. Charoen Pokphand Foods |
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 Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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