Correlation Between Green Cross and Busan Industrial
Can any of the company-specific risk be diversified away by investing in both Green Cross and Busan Industrial 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 Green Cross and Busan Industrial into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Green Cross Medical and Busan Industrial Co, you can compare the effects of market volatilities on Green Cross and Busan Industrial 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 Green Cross with a short position of Busan Industrial. Check out your portfolio center. Please also check ongoing floating volatility patterns of Green Cross and Busan Industrial.
Diversification Opportunities for Green Cross and Busan Industrial
-0.06 | Correlation Coefficient |
Good diversification
The 3 months correlation between Green and Busan is -0.06. Overlapping area represents the amount of risk that can be diversified away by holding Green Cross Medical and Busan Industrial Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Busan Industrial and Green Cross 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 Green Cross Medical are associated (or correlated) with Busan Industrial. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Busan Industrial has no effect on the direction of Green Cross i.e., Green Cross and Busan Industrial go up and down completely randomly.
Pair Corralation between Green Cross and Busan Industrial
Assuming the 90 days trading horizon Green Cross Medical is expected to under-perform the Busan Industrial. But the stock apears to be less risky and, when comparing its historical volatility, Green Cross Medical is 2.47 times less risky than Busan Industrial. The stock trades about -0.15 of its potential returns per unit of risk. The Busan Industrial Co is currently generating about 0.08 of returns per unit of risk over similar time horizon. If you would invest 5,280,000 in Busan Industrial Co on August 29, 2024 and sell it today you would earn a total of 400,000 from holding Busan Industrial Co or generate 7.58% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Green Cross Medical vs. Busan Industrial Co
Performance |
Timeline |
Green Cross Medical |
Busan Industrial |
Green Cross and Busan Industrial Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Green Cross and Busan Industrial
The main advantage of trading using opposite Green Cross and Busan Industrial positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Green Cross position performs unexpectedly, Busan Industrial 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 Busan Industrial will offset losses from the drop in Busan Industrial's long position.Green Cross vs. Samsung Electronics Co | Green Cross vs. Samsung Electronics Co | Green Cross vs. LG Energy Solution | Green Cross vs. SK Hynix |
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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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