Correlation Between First Insurance and Great China
Can any of the company-specific risk be diversified away by investing in both First Insurance and Great China 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 First Insurance and Great China into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between First Insurance Co and Great China Metal, you can compare the effects of market volatilities on First Insurance and Great China 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 First Insurance with a short position of Great China. Check out your portfolio center. Please also check ongoing floating volatility patterns of First Insurance and Great China.
Diversification Opportunities for First Insurance and Great China
-0.01 | Correlation Coefficient |
Good diversification
The 3 months correlation between First and Great is -0.01. Overlapping area represents the amount of risk that can be diversified away by holding First Insurance Co and Great China Metal in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Great China Metal and First Insurance 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 First Insurance Co are associated (or correlated) with Great China. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Great China Metal has no effect on the direction of First Insurance i.e., First Insurance and Great China go up and down completely randomly.
Pair Corralation between First Insurance and Great China
Assuming the 90 days trading horizon First Insurance Co is expected to generate 2.26 times more return on investment than Great China. However, First Insurance is 2.26 times more volatile than Great China Metal. It trades about 0.21 of its potential returns per unit of risk. Great China Metal is currently generating about 0.0 per unit of risk. If you would invest 2,255 in First Insurance Co on September 15, 2024 and sell it today you would earn a total of 260.00 from holding First Insurance Co or generate 11.53% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
First Insurance Co vs. Great China Metal
Performance |
Timeline |
First Insurance |
Great China Metal |
First Insurance and Great China Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with First Insurance and Great China
The main advantage of trading using opposite First Insurance and Great China positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if First Insurance position performs unexpectedly, Great China 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 Great China will offset losses from the drop in Great China's long position.First Insurance vs. Central Reinsurance Corp | First Insurance vs. Huaku Development Co | First Insurance vs. Fubon Financial Holding | First Insurance vs. Chailease Holding Co |
Great China vs. Taiwan Hon Chuan | Great China vs. Taiwan Secom Co | Great China vs. Taiwan Fu Hsing | Great China vs. Taiwan Shin Kong |
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 Insider Screener module to find insiders across different sectors to evaluate their impact on performance.
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