Correlation Between Kakaopay Corp and Hyundai Green
Can any of the company-specific risk be diversified away by investing in both Kakaopay Corp and Hyundai Green 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 Kakaopay Corp and Hyundai Green into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between kakaopay Corp and Hyundai Green Food, you can compare the effects of market volatilities on Kakaopay Corp and Hyundai Green 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 Kakaopay Corp with a short position of Hyundai Green. Check out your portfolio center. Please also check ongoing floating volatility patterns of Kakaopay Corp and Hyundai Green.
Diversification Opportunities for Kakaopay Corp and Hyundai Green
-0.35 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Kakaopay and Hyundai is -0.35. Overlapping area represents the amount of risk that can be diversified away by holding kakaopay Corp and Hyundai Green Food in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hyundai Green Food and Kakaopay Corp 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 kakaopay Corp are associated (or correlated) with Hyundai Green. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hyundai Green Food has no effect on the direction of Kakaopay Corp i.e., Kakaopay Corp and Hyundai Green go up and down completely randomly.
Pair Corralation between Kakaopay Corp and Hyundai Green
Assuming the 90 days trading horizon kakaopay Corp is expected to under-perform the Hyundai Green. In addition to that, Kakaopay Corp is 2.01 times more volatile than Hyundai Green Food. It trades about -0.05 of its total potential returns per unit of risk. Hyundai Green Food is currently generating about 0.04 per unit of volatility. If you would invest 1,139,000 in Hyundai Green Food on September 2, 2024 and sell it today you would earn a total of 236,000 from holding Hyundai Green Food or generate 20.72% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 83.26% |
| Values | Daily Returns |
kakaopay Corp vs. Hyundai Green Food
Performance |
| Timeline |
| kakaopay Corp |
| Hyundai Green Food |
Kakaopay Corp and Hyundai Green Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Kakaopay Corp and Hyundai Green
The main advantage of trading using opposite Kakaopay Corp and Hyundai Green positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Kakaopay Corp position performs unexpectedly, Hyundai Green 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 Hyundai Green will offset losses from the drop in Hyundai Green's long position.| Kakaopay Corp vs. Hyundai Green Food | Kakaopay Corp vs. CKH Food Health | Kakaopay Corp vs. Formetal Co | Kakaopay Corp vs. Taeyang Metal Industrial |
| Hyundai Green vs. Samsung Electronics Co | Hyundai Green vs. Samsung Electronics Co | Hyundai Green vs. LG Energy Solution | Hyundai Green vs. SK Hynix |
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 Analyst Advice module to analyst recommendations and target price estimates broken down by several categories.
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