Correlation Between Seoul Electronics and SIMMTECH
Can any of the company-specific risk be diversified away by investing in both Seoul Electronics and SIMMTECH 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 SIMMTECH 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 SIMMTECH Co, you can compare the effects of market volatilities on Seoul Electronics and SIMMTECH 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 SIMMTECH. Check out your portfolio center. Please also check ongoing floating volatility patterns of Seoul Electronics and SIMMTECH.
Diversification Opportunities for Seoul Electronics and SIMMTECH
0.79 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Seoul and SIMMTECH is 0.79. Overlapping area represents the amount of risk that can be diversified away by holding Seoul Electronics Telecom and SIMMTECH Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on SIMMTECH 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 SIMMTECH. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of SIMMTECH has no effect on the direction of Seoul Electronics i.e., Seoul Electronics and SIMMTECH go up and down completely randomly.
Pair Corralation between Seoul Electronics and SIMMTECH
Assuming the 90 days trading horizon Seoul Electronics Telecom is expected to generate 0.47 times more return on investment than SIMMTECH. However, Seoul Electronics Telecom is 2.12 times less risky than SIMMTECH. It trades about -0.08 of its potential returns per unit of risk. SIMMTECH Co is currently generating about -0.48 per unit of risk. If you would invest 26,100 in Seoul Electronics Telecom on August 28, 2024 and sell it today you would lose (700.00) from holding Seoul Electronics Telecom or give up 2.68% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Seoul Electronics Telecom vs. SIMMTECH Co
Performance |
| Timeline |
| Seoul Electronics Telecom |
| SIMMTECH |
Seoul Electronics and SIMMTECH Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Seoul Electronics and SIMMTECH
The main advantage of trading using opposite Seoul Electronics and SIMMTECH positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Seoul Electronics position performs unexpectedly, SIMMTECH 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 SIMMTECH will offset losses from the drop in SIMMTECH's long position.| Seoul Electronics vs. Samsung Electronics Co | Seoul Electronics vs. Samsung Electronics Co | Seoul Electronics vs. Hyundai Motor Co | Seoul Electronics vs. Hyundai Motor |
| SIMMTECH vs. Shinil Electronics Co | SIMMTECH vs. Seoul Electronics Telecom | SIMMTECH vs. ABCO Electronics Co | SIMMTECH vs. Daekyung Machinery Engineering |
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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