Correlation Between Formosa Plastics and CTBC Financial
Can any of the company-specific risk be diversified away by investing in both Formosa Plastics and CTBC Financial 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 CTBC Financial 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 CTBC Financial Holding, you can compare the effects of market volatilities on Formosa Plastics and CTBC Financial 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 CTBC Financial. Check out your portfolio center. Please also check ongoing floating volatility patterns of Formosa Plastics and CTBC Financial.
Diversification Opportunities for Formosa Plastics and CTBC Financial
0.65 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Formosa and CTBC is 0.65. Overlapping area represents the amount of risk that can be diversified away by holding Formosa Plastics Corp and CTBC Financial Holding in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CTBC Financial Holding 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 CTBC Financial. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CTBC Financial Holding has no effect on the direction of Formosa Plastics i.e., Formosa Plastics and CTBC Financial go up and down completely randomly.
Pair Corralation between Formosa Plastics and CTBC Financial
Assuming the 90 days trading horizon Formosa Plastics Corp is expected to generate 3.55 times more return on investment than CTBC Financial. However, Formosa Plastics is 3.55 times more volatile than CTBC Financial Holding. It trades about 0.05 of its potential returns per unit of risk. CTBC Financial Holding is currently generating about 0.06 per unit of risk. If you would invest 3,700 in Formosa Plastics Corp on December 27, 2024 and sell it today you would earn a total of 195.00 from holding Formosa Plastics Corp or generate 5.27% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Formosa Plastics Corp vs. CTBC Financial Holding
Performance |
Timeline |
Formosa Plastics Corp |
CTBC Financial Holding |
Formosa Plastics and CTBC Financial Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Formosa Plastics and CTBC Financial
The main advantage of trading using opposite Formosa Plastics and CTBC Financial positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Formosa Plastics position performs unexpectedly, CTBC Financial 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 CTBC Financial will offset losses from the drop in CTBC Financial's long position.Formosa Plastics vs. Nan Ya Plastics | Formosa Plastics vs. Formosa Chemicals Fibre | Formosa Plastics vs. China Steel Corp | Formosa Plastics vs. Formosa Petrochemical Corp |
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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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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