Correlation Between Mercuries Life and Hannstar Display
Can any of the company-specific risk be diversified away by investing in both Mercuries Life and Hannstar Display 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 Mercuries Life and Hannstar Display into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mercuries Life Insurance and Hannstar Display Corp, you can compare the effects of market volatilities on Mercuries Life and Hannstar Display 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 Mercuries Life with a short position of Hannstar Display. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mercuries Life and Hannstar Display.
Diversification Opportunities for Mercuries Life and Hannstar Display
0.55 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Mercuries and Hannstar is 0.55. Overlapping area represents the amount of risk that can be diversified away by holding Mercuries Life Insurance and Hannstar Display Corp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hannstar Display Corp and Mercuries Life 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 Mercuries Life Insurance are associated (or correlated) with Hannstar Display. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hannstar Display Corp has no effect on the direction of Mercuries Life i.e., Mercuries Life and Hannstar Display go up and down completely randomly.
Pair Corralation between Mercuries Life and Hannstar Display
Assuming the 90 days trading horizon Mercuries Life Insurance is expected to generate 0.73 times more return on investment than Hannstar Display. However, Mercuries Life Insurance is 1.36 times less risky than Hannstar Display. It trades about 0.06 of its potential returns per unit of risk. Hannstar Display Corp is currently generating about 0.01 per unit of risk. If you would invest 639.00 in Mercuries Life Insurance on December 26, 2024 and sell it today you would earn a total of 23.00 from holding Mercuries Life Insurance or generate 3.6% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Mercuries Life Insurance vs. Hannstar Display Corp
Performance |
Timeline |
Mercuries Life Insurance |
Hannstar Display Corp |
Mercuries Life and Hannstar Display Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Mercuries Life and Hannstar Display
The main advantage of trading using opposite Mercuries Life and Hannstar Display positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mercuries Life position performs unexpectedly, Hannstar Display 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 Hannstar Display will offset losses from the drop in Hannstar Display's long position.Mercuries Life vs. CSBC Corp Taiwan | Mercuries Life vs. Hung Sheng Construction | Mercuries Life vs. Ton Yi Industrial | Mercuries Life vs. De Licacy Industrial |
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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 Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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