Correlation Between Formosa Laboratories and Abnova Taiwan
Can any of the company-specific risk be diversified away by investing in both Formosa Laboratories and Abnova Taiwan 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 Laboratories and Abnova Taiwan into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Formosa Laboratories and Abnova Taiwan Corp, you can compare the effects of market volatilities on Formosa Laboratories and Abnova Taiwan 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 Laboratories with a short position of Abnova Taiwan. Check out your portfolio center. Please also check ongoing floating volatility patterns of Formosa Laboratories and Abnova Taiwan.
Diversification Opportunities for Formosa Laboratories and Abnova Taiwan
0.9 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Formosa and Abnova is 0.9. Overlapping area represents the amount of risk that can be diversified away by holding Formosa Laboratories and Abnova Taiwan Corp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Abnova Taiwan Corp and Formosa Laboratories 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 Laboratories are associated (or correlated) with Abnova Taiwan. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Abnova Taiwan Corp has no effect on the direction of Formosa Laboratories i.e., Formosa Laboratories and Abnova Taiwan go up and down completely randomly.
Pair Corralation between Formosa Laboratories and Abnova Taiwan
Assuming the 90 days trading horizon Formosa Laboratories is expected to generate 2.03 times more return on investment than Abnova Taiwan. However, Formosa Laboratories is 2.03 times more volatile than Abnova Taiwan Corp. It trades about 0.01 of its potential returns per unit of risk. Abnova Taiwan Corp is currently generating about -0.05 per unit of risk. If you would invest 7,440 in Formosa Laboratories on September 15, 2024 and sell it today you would lose (310.00) from holding Formosa Laboratories or give up 4.17% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Formosa Laboratories vs. Abnova Taiwan Corp
Performance |
Timeline |
Formosa Laboratories |
Abnova Taiwan Corp |
Formosa Laboratories and Abnova Taiwan Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Formosa Laboratories and Abnova Taiwan
The main advantage of trading using opposite Formosa Laboratories and Abnova Taiwan positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Formosa Laboratories position performs unexpectedly, Abnova Taiwan 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 Abnova Taiwan will offset losses from the drop in Abnova Taiwan's long position.Formosa Laboratories vs. Adimmune Corp | Formosa Laboratories vs. Chunghwa Chemical Synthesis | Formosa Laboratories vs. SCI Pharmtech | Formosa Laboratories vs. Grape King Bio |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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