Correlation Between POSCO Holdings and GS Engineering
Can any of the company-specific risk be diversified away by investing in both POSCO Holdings and GS Engineering 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 POSCO Holdings and GS Engineering into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between POSCO Holdings and GS Engineering Construction, you can compare the effects of market volatilities on POSCO Holdings and GS Engineering 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 POSCO Holdings with a short position of GS Engineering. Check out your portfolio center. Please also check ongoing floating volatility patterns of POSCO Holdings and GS Engineering.
Diversification Opportunities for POSCO Holdings and GS Engineering
-0.05 | Correlation Coefficient |
Good diversification
The 3 months correlation between POSCO and 006360 is -0.05. Overlapping area represents the amount of risk that can be diversified away by holding POSCO Holdings and GS Engineering Construction in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on GS Engineering Const and POSCO Holdings 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 POSCO Holdings are associated (or correlated) with GS Engineering. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of GS Engineering Const has no effect on the direction of POSCO Holdings i.e., POSCO Holdings and GS Engineering go up and down completely randomly.
Pair Corralation between POSCO Holdings and GS Engineering
Assuming the 90 days trading horizon POSCO Holdings is expected to under-perform the GS Engineering. But the stock apears to be less risky and, when comparing its historical volatility, POSCO Holdings is 1.03 times less risky than GS Engineering. The stock trades about -0.08 of its potential returns per unit of risk. The GS Engineering Construction is currently generating about 0.05 of returns per unit of risk over similar time horizon. If you would invest 1,469,756 in GS Engineering Construction on September 15, 2024 and sell it today you would earn a total of 386,244 from holding GS Engineering Construction or generate 26.28% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
POSCO Holdings vs. GS Engineering Construction
Performance |
Timeline |
POSCO Holdings |
GS Engineering Const |
POSCO Holdings and GS Engineering Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with POSCO Holdings and GS Engineering
The main advantage of trading using opposite POSCO Holdings and GS Engineering positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if POSCO Holdings position performs unexpectedly, GS Engineering 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 GS Engineering will offset losses from the drop in GS Engineering's long position.POSCO Holdings vs. LG Chemicals | POSCO Holdings vs. Hanwha Solutions | POSCO Holdings vs. Lotte Chemical Corp | POSCO Holdings vs. Hyundai Steel |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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