Correlation Between Great China and Formosa International
Can any of the company-specific risk be diversified away by investing in both Great China and Formosa International 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 Great China and Formosa International into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Great China Metal and Formosa International Hotels, you can compare the effects of market volatilities on Great China and Formosa International 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 Great China with a short position of Formosa International. Check out your portfolio center. Please also check ongoing floating volatility patterns of Great China and Formosa International.
Diversification Opportunities for Great China and Formosa International
0.28 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Great and Formosa is 0.28. Overlapping area represents the amount of risk that can be diversified away by holding Great China Metal and Formosa International Hotels in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Formosa International and Great China 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 Great China Metal are associated (or correlated) with Formosa International. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Formosa International has no effect on the direction of Great China i.e., Great China and Formosa International go up and down completely randomly.
Pair Corralation between Great China and Formosa International
Assuming the 90 days trading horizon Great China Metal is expected to generate 0.24 times more return on investment than Formosa International. However, Great China Metal is 4.24 times less risky than Formosa International. It trades about 0.0 of its potential returns per unit of risk. Formosa International Hotels is currently generating about -0.02 per unit of risk. If you would invest 2,317 in Great China Metal on September 26, 2024 and sell it today you would lose (27.00) from holding Great China Metal or give up 1.17% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 99.79% |
Values | Daily Returns |
Great China Metal vs. Formosa International Hotels
Performance |
Timeline |
Great China Metal |
Formosa International |
Great China and Formosa International Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Great China and Formosa International
The main advantage of trading using opposite Great China and Formosa International positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Great China position performs unexpectedly, Formosa International 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 Formosa International will offset losses from the drop in Formosa International's long position.Great China vs. Formosa Chemicals Fibre | Great China vs. China Steel Corp | Great China vs. Formosa Petrochemical Corp | Great China vs. Cathay Financial Holding |
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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 Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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