Correlation Between Poongsan and Busan Industrial
Can any of the company-specific risk be diversified away by investing in both Poongsan 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 Poongsan and Busan Industrial into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Poongsan and Busan Industrial Co, you can compare the effects of market volatilities on Poongsan 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 Poongsan with a short position of Busan Industrial. Check out your portfolio center. Please also check ongoing floating volatility patterns of Poongsan and Busan Industrial.
Diversification Opportunities for Poongsan and Busan Industrial
-0.65 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Poongsan and Busan is -0.65. Overlapping area represents the amount of risk that can be diversified away by holding Poongsan and Busan Industrial Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Busan Industrial and Poongsan 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 Poongsan 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 Poongsan i.e., Poongsan and Busan Industrial go up and down completely randomly.
Pair Corralation between Poongsan and Busan Industrial
Assuming the 90 days trading horizon Poongsan is expected to under-perform the Busan Industrial. But the stock apears to be less risky and, when comparing its historical volatility, Poongsan is 2.39 times less risky than Busan Industrial. The stock trades about -0.09 of its potential returns per unit of risk. The Busan Industrial Co is currently generating about 0.2 of returns per unit of risk over similar time horizon. If you would invest 5,630,000 in Busan Industrial Co on September 25, 2024 and sell it today you would earn a total of 2,090,000 from holding Busan Industrial Co or generate 37.12% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Poongsan vs. Busan Industrial Co
Performance |
| Timeline |
| Poongsan |
| Busan Industrial |
Poongsan and Busan Industrial Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Poongsan and Busan Industrial
The main advantage of trading using opposite Poongsan and Busan Industrial positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Poongsan 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.| Poongsan vs. LG Chemicals | Poongsan vs. POSCO Holdings | Poongsan vs. Hanwha Solutions | Poongsan vs. Lotte Chemical Corp |
| Busan Industrial vs. AptaBio Therapeutics | Busan Industrial vs. Wonbang Tech Co | Busan Industrial vs. Busan Ind | Busan Industrial vs. Mirae Asset Daewoo |
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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