Correlation Between China Metal and Farglory Life
Can any of the company-specific risk be diversified away by investing in both China Metal and Farglory Life 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 China Metal and Farglory Life into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between China Metal Products and Farglory Life Insurance, you can compare the effects of market volatilities on China Metal and Farglory Life 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 China Metal with a short position of Farglory Life. Check out your portfolio center. Please also check ongoing floating volatility patterns of China Metal and Farglory Life.
Diversification Opportunities for China Metal and Farglory Life
0.22 | Correlation Coefficient |
Modest diversification
The 3 months correlation between China and Farglory is 0.22. Overlapping area represents the amount of risk that can be diversified away by holding China Metal Products and Farglory Life Insurance in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Farglory Life Insurance and China Metal 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 China Metal Products are associated (or correlated) with Farglory Life. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Farglory Life Insurance has no effect on the direction of China Metal i.e., China Metal and Farglory Life go up and down completely randomly.
Pair Corralation between China Metal and Farglory Life
Assuming the 90 days trading horizon China Metal Products is expected to under-perform the Farglory Life. But the stock apears to be less risky and, when comparing its historical volatility, China Metal Products is 1.57 times less risky than Farglory Life. The stock trades about -0.36 of its potential returns per unit of risk. The Farglory Life Insurance is currently generating about -0.04 of returns per unit of risk over similar time horizon. If you would invest 1,685 in Farglory Life Insurance on October 9, 2024 and sell it today you would lose (25.00) from holding Farglory Life Insurance or give up 1.48% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
China Metal Products vs. Farglory Life Insurance
Performance |
Timeline |
China Metal Products |
Farglory Life Insurance |
China Metal and Farglory Life Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with China Metal and Farglory Life
The main advantage of trading using opposite China Metal and Farglory Life positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if China Metal position performs unexpectedly, Farglory Life 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 Farglory Life will offset losses from the drop in Farglory Life's long position.China Metal vs. Basso Industry Corp | China Metal vs. Chung Hsin Electric Machinery | China Metal vs. TYC Brother Industrial | China Metal 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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