Correlation Between Hyundai and Edita Food
Can any of the company-specific risk be diversified away by investing in both Hyundai and Edita Food 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 Hyundai and Edita Food into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Hyundai Motor and Edita Food Industries, you can compare the effects of market volatilities on Hyundai and Edita Food 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 Hyundai with a short position of Edita Food. Check out your portfolio center. Please also check ongoing floating volatility patterns of Hyundai and Edita Food.
Diversification Opportunities for Hyundai and Edita Food
0.6 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Hyundai and Edita is 0.6. Overlapping area represents the amount of risk that can be diversified away by holding Hyundai Motor and Edita Food Industries in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Edita Food Industries and Hyundai 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 Hyundai Motor are associated (or correlated) with Edita Food. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Edita Food Industries has no effect on the direction of Hyundai i.e., Hyundai and Edita Food go up and down completely randomly.
Pair Corralation between Hyundai and Edita Food
Assuming the 90 days trading horizon Hyundai is expected to generate 1.62 times less return on investment than Edita Food. But when comparing it to its historical volatility, Hyundai Motor is 1.61 times less risky than Edita Food. It trades about 0.03 of its potential returns per unit of risk. Edita Food Industries is currently generating about 0.03 of returns per unit of risk over similar time horizon. If you would invest 194.00 in Edita Food Industries on August 29, 2024 and sell it today you would earn a total of 6.00 from holding Edita Food Industries or generate 3.09% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Hyundai Motor vs. Edita Food Industries
Performance |
| Timeline |
| Hyundai Motor |
| Edita Food Industries |
Hyundai and Edita Food Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Hyundai and Edita Food
The main advantage of trading using opposite Hyundai and Edita Food positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Hyundai position performs unexpectedly, Edita Food 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 Edita Food will offset losses from the drop in Edita Food's long position.| Hyundai vs. Ondine Biomedical | Hyundai vs. Europa Metals | Hyundai vs. Lendinvest PLC | Hyundai vs. Neometals |
| Edita Food vs. Samsung Electronics Co | Edita Food vs. Samsung Electronics Co | Edita Food vs. Toyota Motor Corp | Edita Food vs. Reliance Industries Ltd |
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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