Correlation Between POSCO Holdings and Daehan Synthetic
Can any of the company-specific risk be diversified away by investing in both POSCO Holdings and Daehan Synthetic 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 Daehan Synthetic into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between POSCO Holdings and Daehan Synthetic Fiber, you can compare the effects of market volatilities on POSCO Holdings and Daehan Synthetic 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 Daehan Synthetic. Check out your portfolio center. Please also check ongoing floating volatility patterns of POSCO Holdings and Daehan Synthetic.
Diversification Opportunities for POSCO Holdings and Daehan Synthetic
0.03 | Correlation Coefficient |
Significant diversification
The 3 months correlation between POSCO and Daehan is 0.03. Overlapping area represents the amount of risk that can be diversified away by holding POSCO Holdings and Daehan Synthetic Fiber in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Daehan Synthetic Fiber 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 Daehan Synthetic. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Daehan Synthetic Fiber has no effect on the direction of POSCO Holdings i.e., POSCO Holdings and Daehan Synthetic go up and down completely randomly.
Pair Corralation between POSCO Holdings and Daehan Synthetic
Assuming the 90 days trading horizon POSCO Holdings is expected to under-perform the Daehan Synthetic. In addition to that, POSCO Holdings is 5.38 times more volatile than Daehan Synthetic Fiber. It trades about -0.14 of its total potential returns per unit of risk. Daehan Synthetic Fiber is currently generating about -0.21 per unit of volatility. If you would invest 11,490,000 in Daehan Synthetic Fiber on September 12, 2024 and sell it today you would lose (390,000) from holding Daehan Synthetic Fiber or give up 3.39% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
POSCO Holdings vs. Daehan Synthetic Fiber
Performance |
Timeline |
POSCO Holdings |
Daehan Synthetic Fiber |
POSCO Holdings and Daehan Synthetic Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with POSCO Holdings and Daehan Synthetic
The main advantage of trading using opposite POSCO Holdings and Daehan Synthetic positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if POSCO Holdings position performs unexpectedly, Daehan Synthetic 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 Daehan Synthetic will offset losses from the drop in Daehan Synthetic'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 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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