Correlation Between POSCO Holdings and Africa Energy
Can any of the company-specific risk be diversified away by investing in both POSCO Holdings and Africa Energy 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 Africa Energy into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between POSCO Holdings and Africa Energy Corp, you can compare the effects of market volatilities on POSCO Holdings and Africa Energy 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 Africa Energy. Check out your portfolio center. Please also check ongoing floating volatility patterns of POSCO Holdings and Africa Energy.
Diversification Opportunities for POSCO Holdings and Africa Energy
0.03 | Correlation Coefficient |
Significant diversification
The 3 months correlation between POSCO and Africa is 0.03. Overlapping area represents the amount of risk that can be diversified away by holding POSCO Holdings and Africa Energy Corp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Africa Energy Corp 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 Africa Energy. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Africa Energy Corp has no effect on the direction of POSCO Holdings i.e., POSCO Holdings and Africa Energy go up and down completely randomly.
Pair Corralation between POSCO Holdings and Africa Energy
Considering the 90-day investment horizon POSCO Holdings is expected to generate 6.75 times less return on investment than Africa Energy. But when comparing it to its historical volatility, POSCO Holdings is 2.61 times less risky than Africa Energy. It trades about 0.1 of its potential returns per unit of risk. Africa Energy Corp is currently generating about 0.25 of returns per unit of risk over similar time horizon. If you would invest 1.70 in Africa Energy Corp on December 2, 2024 and sell it today you would earn a total of 1.30 from holding Africa Energy Corp or generate 76.47% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
POSCO Holdings vs. Africa Energy Corp
Performance |
Timeline |
POSCO Holdings |
Africa Energy Corp |
POSCO Holdings and Africa Energy Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with POSCO Holdings and Africa Energy
The main advantage of trading using opposite POSCO Holdings and Africa Energy positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if POSCO Holdings position performs unexpectedly, Africa Energy 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 Africa Energy will offset losses from the drop in Africa Energy's long position.POSCO Holdings vs. Olympic Steel | POSCO Holdings vs. Outokumpu Oyj ADR | POSCO Holdings vs. Ternium SA ADR | POSCO Holdings vs. Steel Dynamics |
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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 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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