Correlation Between Hung Sheng and First Insurance
Can any of the company-specific risk be diversified away by investing in both Hung Sheng and First Insurance 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 Hung Sheng and First Insurance into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Hung Sheng Construction and First Insurance Co, you can compare the effects of market volatilities on Hung Sheng and First Insurance 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 Hung Sheng with a short position of First Insurance. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hung Sheng and First Insurance.
Diversification Opportunities for Hung Sheng and First Insurance
0.49 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Hung and First is 0.49. Overlapping area represents the amount of risk that can be diversified away by holding Hung Sheng Construction and First Insurance Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on First Insurance and Hung Sheng 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 Hung Sheng Construction are associated (or correlated) with First Insurance. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of First Insurance has no effect on the direction of Hung Sheng i.e., Hung Sheng and First Insurance go up and down completely randomly.
Pair Corralation between Hung Sheng and First Insurance
Assuming the 90 days trading horizon Hung Sheng Construction is expected to under-perform the First Insurance. But the stock apears to be less risky and, when comparing its historical volatility, Hung Sheng Construction is 1.15 times less risky than First Insurance. The stock trades about -0.49 of its potential returns per unit of risk. The First Insurance Co is currently generating about -0.12 of returns per unit of risk over similar time horizon. If you would invest 2,565 in First Insurance Co on October 8, 2024 and sell it today you would lose (60.00) from holding First Insurance Co or give up 2.34% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Hung Sheng Construction vs. First Insurance Co
Performance |
Timeline |
Hung Sheng Construction |
First Insurance |
Hung Sheng and First Insurance Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Hung Sheng and First Insurance
The main advantage of trading using opposite Hung Sheng and First Insurance positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hung Sheng position performs unexpectedly, First Insurance 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 First Insurance will offset losses from the drop in First Insurance's long position.Hung Sheng vs. Shining Building Business | Hung Sheng vs. Chong Hong Construction | Hung Sheng vs. Farglory Land Development | Hung Sheng vs. Sweeten Real Estate |
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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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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