Correlation Between KG Eco and Samsung Electronics
Can any of the company-specific risk be diversified away by investing in both KG Eco and Samsung Electronics 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 KG Eco and Samsung Electronics into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between KG Eco Technology and Samsung Electronics Co, you can compare the effects of market volatilities on KG Eco and Samsung Electronics 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 KG Eco with a short position of Samsung Electronics. Check out your portfolio center. Please also check ongoing floating volatility patterns of KG Eco and Samsung Electronics.
Diversification Opportunities for KG Eco and Samsung Electronics
0.71 | Correlation Coefficient |
Poor diversification
The 3 months correlation between 151860 and Samsung is 0.71. Overlapping area represents the amount of risk that can be diversified away by holding KG Eco Technology and Samsung Electronics Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Samsung Electronics and KG Eco 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 KG Eco Technology are associated (or correlated) with Samsung Electronics. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Samsung Electronics has no effect on the direction of KG Eco i.e., KG Eco and Samsung Electronics go up and down completely randomly.
Pair Corralation between KG Eco and Samsung Electronics
Assuming the 90 days trading horizon KG Eco Technology is expected to under-perform the Samsung Electronics. In addition to that, KG Eco is 2.12 times more volatile than Samsung Electronics Co. It trades about -0.05 of its total potential returns per unit of risk. Samsung Electronics Co is currently generating about 0.0 per unit of volatility. If you would invest 5,752,837 in Samsung Electronics Co on December 2, 2024 and sell it today you would lose (302,837) from holding Samsung Electronics Co or give up 5.26% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 99.58% |
Values | Daily Returns |
KG Eco Technology vs. Samsung Electronics Co
Performance |
Timeline |
KG Eco Technology |
Samsung Electronics |
KG Eco and Samsung Electronics Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with KG Eco and Samsung Electronics
The main advantage of trading using opposite KG Eco and Samsung Electronics positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if KG Eco position performs unexpectedly, Samsung Electronics 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 Samsung Electronics will offset losses from the drop in Samsung Electronics' long position.KG Eco vs. E Investment Development | KG Eco vs. Golden Bridge Investment | KG Eco vs. Jin Air Co | KG Eco vs. Mgame Corp |
Samsung Electronics vs. Woori Financial Group | Samsung Electronics vs. Lotte Data Communication | Samsung Electronics vs. Jeju Bank | Samsung Electronics vs. Hana Financial |
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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