Correlation Between Hwa Fong and Ekarat Engineering
Can any of the company-specific risk be diversified away by investing in both Hwa Fong and Ekarat Engineering 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 Hwa Fong and Ekarat Engineering into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Hwa Fong Rubber and Ekarat Engineering Public, you can compare the effects of market volatilities on Hwa Fong and Ekarat Engineering 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 Hwa Fong with a short position of Ekarat Engineering. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hwa Fong and Ekarat Engineering.
Diversification Opportunities for Hwa Fong and Ekarat Engineering
0.95 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Hwa and Ekarat is 0.95. Overlapping area represents the amount of risk that can be diversified away by holding Hwa Fong Rubber and Ekarat Engineering Public in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Ekarat Engineering Public and Hwa Fong 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 Hwa Fong Rubber are associated (or correlated) with Ekarat Engineering. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Ekarat Engineering Public has no effect on the direction of Hwa Fong i.e., Hwa Fong and Ekarat Engineering go up and down completely randomly.
Pair Corralation between Hwa Fong and Ekarat Engineering
Assuming the 90 days trading horizon Hwa Fong Rubber is expected to under-perform the Ekarat Engineering. But the stock apears to be less risky and, when comparing its historical volatility, Hwa Fong Rubber is 1.05 times less risky than Ekarat Engineering. The stock trades about -0.25 of its potential returns per unit of risk. The Ekarat Engineering Public is currently generating about 0.04 of returns per unit of risk over similar time horizon. If you would invest 91.00 in Ekarat Engineering Public on September 3, 2024 and sell it today you would earn a total of 1.00 from holding Ekarat Engineering Public or generate 1.1% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Hwa Fong Rubber vs. Ekarat Engineering Public
Performance |
| Timeline |
| Hwa Fong Rubber |
| Ekarat Engineering Public |
Hwa Fong and Ekarat Engineering Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Hwa Fong and Ekarat Engineering
The main advantage of trading using opposite Hwa Fong and Ekarat Engineering positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hwa Fong position performs unexpectedly, Ekarat Engineering 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 Ekarat Engineering will offset losses from the drop in Ekarat Engineering's long position.| Hwa Fong vs. Haad Thip Public | Hwa Fong vs. AAPICO Hitech Public | Hwa Fong vs. Inoue Rubber Public | Hwa Fong vs. Hana Microelectronics Public |
| Ekarat Engineering vs. JD Food PCL | Ekarat Engineering vs. Mena Transport Public | Ekarat Engineering vs. KTBST Mixed Leasehold | Ekarat Engineering vs. Quality Construction Products |
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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