Correlation Between Formosa Plastics and Delta Electronics
Can any of the company-specific risk be diversified away by investing in both Formosa Plastics and Delta Electronics 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 Delta Electronics 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 Delta Electronics, you can compare the effects of market volatilities on Formosa Plastics and Delta Electronics 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 Delta Electronics. Check out your portfolio center. Please also check ongoing floating volatility patterns of Formosa Plastics and Delta Electronics.
Diversification Opportunities for Formosa Plastics and Delta Electronics
0.08 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Formosa and Delta is 0.08. Overlapping area represents the amount of risk that can be diversified away by holding Formosa Plastics Corp and Delta Electronics in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Delta Electronics 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 Delta Electronics. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Delta Electronics has no effect on the direction of Formosa Plastics i.e., Formosa Plastics and Delta Electronics go up and down completely randomly.
Pair Corralation between Formosa Plastics and Delta Electronics
Assuming the 90 days trading horizon Formosa Plastics Corp is expected to under-perform the Delta Electronics. In addition to that, Formosa Plastics is 1.13 times more volatile than Delta Electronics. It trades about -0.13 of its total potential returns per unit of risk. Delta Electronics is currently generating about -0.02 per unit of volatility. If you would invest 39,450 in Delta Electronics on August 31, 2024 and sell it today you would lose (1,350) from holding Delta Electronics or give up 3.42% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Formosa Plastics Corp vs. Delta Electronics
Performance |
Timeline |
Formosa Plastics Corp |
Delta Electronics |
Formosa Plastics and Delta Electronics Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Formosa Plastics and Delta Electronics
The main advantage of trading using opposite Formosa Plastics and Delta Electronics positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Formosa Plastics position performs unexpectedly, Delta Electronics 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 Delta Electronics will offset losses from the drop in Delta Electronics' 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 |
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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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