Correlation Between Sungdo Engineering and Sempio Foods
Can any of the company-specific risk be diversified away by investing in both Sungdo Engineering and Sempio Foods 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 Sungdo Engineering and Sempio Foods into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Sungdo Engineering Construction and Sempio Foods Co, you can compare the effects of market volatilities on Sungdo Engineering and Sempio Foods 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 Sungdo Engineering with a short position of Sempio Foods. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sungdo Engineering and Sempio Foods.
Diversification Opportunities for Sungdo Engineering and Sempio Foods
0.42 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Sungdo and Sempio is 0.42. Overlapping area represents the amount of risk that can be diversified away by holding Sungdo Engineering Constructio and Sempio Foods Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Sempio Foods and Sungdo Engineering 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 Sungdo Engineering Construction are associated (or correlated) with Sempio Foods. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Sempio Foods has no effect on the direction of Sungdo Engineering i.e., Sungdo Engineering and Sempio Foods go up and down completely randomly.
Pair Corralation between Sungdo Engineering and Sempio Foods
Assuming the 90 days trading horizon Sungdo Engineering Construction is expected to generate 1.1 times more return on investment than Sempio Foods. However, Sungdo Engineering is 1.1 times more volatile than Sempio Foods Co. It trades about 0.29 of its potential returns per unit of risk. Sempio Foods Co is currently generating about 0.15 per unit of risk. If you would invest 424,000 in Sungdo Engineering Construction on October 11, 2024 and sell it today you would earn a total of 56,000 from holding Sungdo Engineering Construction or generate 13.21% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Sungdo Engineering Constructio vs. Sempio Foods Co
Performance |
Timeline |
Sungdo Engineering |
Sempio Foods |
Sungdo Engineering and Sempio Foods Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Sungdo Engineering and Sempio Foods
The main advantage of trading using opposite Sungdo Engineering and Sempio Foods positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sungdo Engineering position performs unexpectedly, Sempio Foods 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 Sempio Foods will offset losses from the drop in Sempio Foods' long position.Sungdo Engineering vs. Iljin Display | Sungdo Engineering vs. PlayD Co | Sungdo Engineering vs. PJ Electronics Co | Sungdo Engineering vs. Cuckoo Electronics Co |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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