Correlation Between Seoul Electronics and Jeong Moon
Can any of the company-specific risk be diversified away by investing in both Seoul Electronics and Jeong Moon 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 Seoul Electronics and Jeong Moon into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Seoul Electronics Telecom and Jeong Moon Information, you can compare the effects of market volatilities on Seoul Electronics and Jeong Moon 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 Seoul Electronics with a short position of Jeong Moon. Check out your portfolio center. Please also check ongoing floating volatility patterns of Seoul Electronics and Jeong Moon.
Diversification Opportunities for Seoul Electronics and Jeong Moon
0.66 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Seoul and Jeong is 0.66. Overlapping area represents the amount of risk that can be diversified away by holding Seoul Electronics Telecom and Jeong Moon Information in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Jeong Moon Information and Seoul Electronics 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 Seoul Electronics Telecom are associated (or correlated) with Jeong Moon. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Jeong Moon Information has no effect on the direction of Seoul Electronics i.e., Seoul Electronics and Jeong Moon go up and down completely randomly.
Pair Corralation between Seoul Electronics and Jeong Moon
Assuming the 90 days trading horizon Seoul Electronics Telecom is expected to generate 1.98 times more return on investment than Jeong Moon. However, Seoul Electronics is 1.98 times more volatile than Jeong Moon Information. It trades about 0.05 of its potential returns per unit of risk. Jeong Moon Information is currently generating about 0.03 per unit of risk. If you would invest 23,300 in Seoul Electronics Telecom on November 3, 2024 and sell it today you would earn a total of 500.00 from holding Seoul Electronics Telecom or generate 2.15% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Seoul Electronics Telecom vs. Jeong Moon Information
Performance |
Timeline |
Seoul Electronics Telecom |
Jeong Moon Information |
Seoul Electronics and Jeong Moon Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Seoul Electronics and Jeong Moon
The main advantage of trading using opposite Seoul Electronics and Jeong Moon positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Seoul Electronics position performs unexpectedly, Jeong Moon 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 Jeong Moon will offset losses from the drop in Jeong Moon's long position.Seoul Electronics vs. MetaLabs Co | Seoul Electronics vs. Youngsin Metal Industrial | Seoul Electronics vs. DONGKUK TED METAL | Seoul Electronics vs. Shinhan Inverse Copper |
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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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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