Correlation Between Formosa Chemicals and U Ming
Can any of the company-specific risk be diversified away by investing in both Formosa Chemicals and U Ming 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 Formosa Chemicals and U Ming into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Formosa Chemicals Fibre and U Ming Marine Transport, you can compare the effects of market volatilities on Formosa Chemicals and U Ming 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 Formosa Chemicals with a short position of U Ming. Check out your portfolio center. Please also check ongoing floating volatility patterns of Formosa Chemicals and U Ming.
Diversification Opportunities for Formosa Chemicals and U Ming
-0.1 | Correlation Coefficient |
Good diversification
The 3 months correlation between Formosa and 2606 is -0.1. Overlapping area represents the amount of risk that can be diversified away by holding Formosa Chemicals Fibre and U Ming Marine Transport in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on U Ming Marine and Formosa Chemicals 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 Formosa Chemicals Fibre are associated (or correlated) with U Ming. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of U Ming Marine has no effect on the direction of Formosa Chemicals i.e., Formosa Chemicals and U Ming go up and down completely randomly.
Pair Corralation between Formosa Chemicals and U Ming
Assuming the 90 days trading horizon Formosa Chemicals Fibre is expected to under-perform the U Ming. In addition to that, Formosa Chemicals is 1.17 times more volatile than U Ming Marine Transport. It trades about -0.05 of its total potential returns per unit of risk. U Ming Marine Transport is currently generating about 0.22 per unit of volatility. If you would invest 5,380 in U Ming Marine Transport on October 22, 2024 and sell it today you would earn a total of 540.00 from holding U Ming Marine Transport or generate 10.04% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 95.24% |
| Values | Daily Returns |
Formosa Chemicals Fibre vs. U Ming Marine Transport
Performance |
| Timeline |
| Formosa Chemicals Fibre |
| U Ming Marine |
Formosa Chemicals and U Ming Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Formosa Chemicals and U Ming
The main advantage of trading using opposite Formosa Chemicals and U Ming positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Formosa Chemicals position performs unexpectedly, U Ming 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 U Ming will offset losses from the drop in U Ming's long position.| Formosa Chemicals vs. Formosa Plastics Corp | Formosa Chemicals vs. Nan Ya Plastics | Formosa Chemicals vs. Formosa Petrochemical Corp | Formosa Chemicals vs. Cathay Financial Holding |
| U Ming vs. Sincere Navigation Corp | U Ming vs. Wan Hai Lines | U Ming vs. Yang Ming Marine | U Ming vs. Formosa Chemicals Fibre |
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 Optimization module to compute new portfolio that will generate highest expected return given your specified tolerance for risk.
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