Correlation Between Mercuries Data and Lian Hwa
Can any of the company-specific risk be diversified away by investing in both Mercuries Data and Lian Hwa 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 Data and Lian Hwa into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Mercuries Data Systems and Lian Hwa Foods, you can compare the effects of market volatilities on Mercuries Data and Lian Hwa 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 Data with a short position of Lian Hwa. Check out your portfolio center. Please also check ongoing floating volatility patterns of Mercuries Data and Lian Hwa.
Diversification Opportunities for Mercuries Data and Lian Hwa
0.04 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Mercuries and Lian is 0.04. Overlapping area represents the amount of risk that can be diversified away by holding Mercuries Data Systems and Lian Hwa Foods in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Lian Hwa Foods and Mercuries Data 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 Data Systems are associated (or correlated) with Lian Hwa. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Lian Hwa Foods has no effect on the direction of Mercuries Data i.e., Mercuries Data and Lian Hwa go up and down completely randomly.
Pair Corralation between Mercuries Data and Lian Hwa
Assuming the 90 days trading horizon Mercuries Data Systems is expected to under-perform the Lian Hwa. In addition to that, Mercuries Data is 1.14 times more volatile than Lian Hwa Foods. It trades about -0.13 of its total potential returns per unit of risk. Lian Hwa Foods is currently generating about 0.22 per unit of volatility. If you would invest 11,250 in Lian Hwa Foods on August 31, 2024 and sell it today you would earn a total of 750.00 from holding Lian Hwa Foods or generate 6.67% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Mercuries Data Systems vs. Lian Hwa Foods
Performance |
| Timeline |
| Mercuries Data Systems |
| Lian Hwa Foods |
Mercuries Data and Lian Hwa Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Mercuries Data and Lian Hwa
The main advantage of trading using opposite Mercuries Data and Lian Hwa positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Mercuries Data position performs unexpectedly, Lian Hwa 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 Lian Hwa will offset losses from the drop in Lian Hwa's long position.| Mercuries Data vs. United Microelectronics | Mercuries Data vs. Winbond Electronics Corp | Mercuries Data vs. Macronix International Co |
| Lian Hwa vs. Taisun Enterprise Co | Lian Hwa vs. De Licacy Industrial | Lian Hwa vs. Wisher Industrial Co | Lian Hwa vs. Tainan Enterprises Co |
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 Instant Ratings module to determine any equity ratings based on digital recommendations. Macroaxis instant equity ratings are based on combination of fundamental analysis and risk-adjusted market performance.
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