Correlation Between Delta Electronics and Bangkok Bank
Can any of the company-specific risk be diversified away by investing in both Delta Electronics and Bangkok Bank 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 Delta Electronics and Bangkok Bank into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Delta Electronics Public and Bangkok Bank Public, you can compare the effects of market volatilities on Delta Electronics and Bangkok Bank 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 Delta Electronics with a short position of Bangkok Bank. Check out your portfolio center. Please also check ongoing floating volatility patterns of Delta Electronics and Bangkok Bank.
Diversification Opportunities for Delta Electronics and Bangkok Bank
-0.54 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Delta and Bangkok is -0.54. Overlapping area represents the amount of risk that can be diversified away by holding Delta Electronics Public and Bangkok Bank Public in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Bangkok Bank Public and Delta Electronics 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 Delta Electronics Public are associated (or correlated) with Bangkok Bank. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Bangkok Bank Public has no effect on the direction of Delta Electronics i.e., Delta Electronics and Bangkok Bank go up and down completely randomly.
Pair Corralation between Delta Electronics and Bangkok Bank
Assuming the 90 days trading horizon Delta Electronics Public is expected to generate 2.85 times more return on investment than Bangkok Bank. However, Delta Electronics is 2.85 times more volatile than Bangkok Bank Public. It trades about 0.21 of its potential returns per unit of risk. Bangkok Bank Public is currently generating about -0.03 per unit of risk. If you would invest 10,400 in Delta Electronics Public on September 12, 2024 and sell it today you would earn a total of 4,700 from holding Delta Electronics Public or generate 45.19% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Delta Electronics Public vs. Bangkok Bank Public
Performance |
Timeline |
Delta Electronics Public |
Bangkok Bank Public |
Delta Electronics and Bangkok Bank Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Delta Electronics and Bangkok Bank
The main advantage of trading using opposite Delta Electronics and Bangkok Bank positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Delta Electronics position performs unexpectedly, Bangkok Bank 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 Bangkok Bank will offset losses from the drop in Bangkok Bank's long position.Delta Electronics vs. Airports of Thailand | Delta Electronics vs. Hana Microelectronics Public | Delta Electronics vs. Advanced Info Service | Delta Electronics vs. Kasikornbank 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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