Correlation Between Thai Stanley and Somboon Advance
Can any of the company-specific risk be diversified away by investing in both Thai Stanley and Somboon Advance 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 Thai Stanley and Somboon Advance into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Thai Stanley Electric and Somboon Advance Technology, you can compare the effects of market volatilities on Thai Stanley and Somboon Advance 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 Thai Stanley with a short position of Somboon Advance. Check out your portfolio center. Please also check ongoing floating volatility patterns of Thai Stanley and Somboon Advance.
Diversification Opportunities for Thai Stanley and Somboon Advance
0.13 | Correlation Coefficient |
Average diversification
The 3 months correlation between Thai and Somboon is 0.13. Overlapping area represents the amount of risk that can be diversified away by holding Thai Stanley Electric and Somboon Advance Technology in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Somboon Advance Tech and Thai Stanley 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 Thai Stanley Electric are associated (or correlated) with Somboon Advance. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Somboon Advance Tech has no effect on the direction of Thai Stanley i.e., Thai Stanley and Somboon Advance go up and down completely randomly.
Pair Corralation between Thai Stanley and Somboon Advance
Assuming the 90 days trading horizon Thai Stanley Electric is expected to generate 0.52 times more return on investment than Somboon Advance. However, Thai Stanley Electric is 1.93 times less risky than Somboon Advance. It trades about 0.0 of its potential returns per unit of risk. Somboon Advance Technology is currently generating about -0.42 per unit of risk. If you would invest 21,800 in Thai Stanley Electric on August 31, 2024 and sell it today you would earn a total of 0.00 from holding Thai Stanley Electric or generate 0.0% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Thai Stanley Electric vs. Somboon Advance Technology
Performance |
| Timeline |
| Thai Stanley Electric |
| Somboon Advance Tech |
Thai Stanley and Somboon Advance Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Thai Stanley and Somboon Advance
The main advantage of trading using opposite Thai Stanley and Somboon Advance positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Thai Stanley position performs unexpectedly, Somboon Advance 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 Somboon Advance will offset losses from the drop in Somboon Advance's long position.| Thai Stanley vs. Somboon Advance Technology | Thai Stanley vs. TISCO Financial Group | Thai Stanley vs. Quality Houses Public | Thai Stanley vs. Hana Microelectronics 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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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