Correlation Between Formosa Plastics and Chunghwa Telecom
Can any of the company-specific risk be diversified away by investing in both Formosa Plastics and Chunghwa Telecom 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 Plastics and Chunghwa Telecom into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Formosa Plastics Corp and Chunghwa Telecom Co, you can compare the effects of market volatilities on Formosa Plastics and Chunghwa Telecom 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 Plastics with a short position of Chunghwa Telecom. Check out your portfolio center. Please also check ongoing floating volatility patterns of Formosa Plastics and Chunghwa Telecom.
Diversification Opportunities for Formosa Plastics and Chunghwa Telecom
0.48 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Formosa and Chunghwa is 0.48. Overlapping area represents the amount of risk that can be diversified away by holding Formosa Plastics Corp and Chunghwa Telecom Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Chunghwa Telecom and Formosa Plastics 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 Plastics Corp are associated (or correlated) with Chunghwa Telecom. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Chunghwa Telecom has no effect on the direction of Formosa Plastics i.e., Formosa Plastics and Chunghwa Telecom go up and down completely randomly.
Pair Corralation between Formosa Plastics and Chunghwa Telecom
Assuming the 90 days trading horizon Formosa Plastics Corp is expected to under-perform the Chunghwa Telecom. In addition to that, Formosa Plastics is 3.92 times more volatile than Chunghwa Telecom Co. It trades about -0.13 of its total potential returns per unit of risk. Chunghwa Telecom Co is currently generating about -0.02 per unit of volatility. If you would invest 12,400 in Chunghwa Telecom Co on September 2, 2024 and sell it today you would lose (100.00) from holding Chunghwa Telecom Co or give up 0.81% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Formosa Plastics Corp vs. Chunghwa Telecom Co
Performance |
Timeline |
Formosa Plastics Corp |
Chunghwa Telecom |
Formosa Plastics and Chunghwa Telecom Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Formosa Plastics and Chunghwa Telecom
The main advantage of trading using opposite Formosa Plastics and Chunghwa Telecom positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Formosa Plastics position performs unexpectedly, Chunghwa Telecom 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 Chunghwa Telecom will offset losses from the drop in Chunghwa Telecom's long position.Formosa Plastics vs. Basso Industry Corp | Formosa Plastics vs. Chung Hsin Electric Machinery | Formosa Plastics vs. TYC Brother Industrial | Formosa Plastics vs. TECO Electric Machinery |
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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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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