Correlation Between Krung Thai and Professional Waste
Can any of the company-specific risk be diversified away by investing in both Krung Thai and Professional Waste 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 Krung Thai and Professional Waste into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Krung Thai Bank and Professional Waste Technology, you can compare the effects of market volatilities on Krung Thai and Professional Waste 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 Krung Thai with a short position of Professional Waste. Check out your portfolio center. Please also check ongoing floating volatility patterns of Krung Thai and Professional Waste.
Diversification Opportunities for Krung Thai and Professional Waste
-0.69 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Krung and Professional is -0.69. Overlapping area represents the amount of risk that can be diversified away by holding Krung Thai Bank and Professional Waste Technology in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Professional Waste and Krung 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 Krung Thai Bank are associated (or correlated) with Professional Waste. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Professional Waste has no effect on the direction of Krung Thai i.e., Krung Thai and Professional Waste go up and down completely randomly.
Pair Corralation between Krung Thai and Professional Waste
Assuming the 90 days trading horizon Krung Thai Bank is expected to generate 0.03 times more return on investment than Professional Waste. However, Krung Thai Bank is 28.96 times less risky than Professional Waste. It trades about 0.25 of its potential returns per unit of risk. Professional Waste Technology is currently generating about -0.18 per unit of risk. If you would invest 2,100 in Krung Thai Bank on November 3, 2024 and sell it today you would earn a total of 190.00 from holding Krung Thai Bank or generate 9.05% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 30.43% |
| Values | Daily Returns |
Krung Thai Bank vs. Professional Waste Technology
Performance |
| Timeline |
| Krung Thai Bank |
| Professional Waste |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
Krung Thai and Professional Waste Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Krung Thai and Professional Waste
The main advantage of trading using opposite Krung Thai and Professional Waste positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Krung Thai position performs unexpectedly, Professional Waste 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 Professional Waste will offset losses from the drop in Professional Waste's long position.| Krung Thai vs. The Siam Commercial | Krung Thai vs. Thai Union Group | Krung Thai vs. Kasikornbank Public | Krung Thai vs. The Siam Cement |
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 Fundamental Analysis module to view fundamental data based on most recent published financial statements.
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