Correlation Between Shinhan Inverse and Poongsan
Can any of the company-specific risk be diversified away by investing in both Shinhan Inverse and Poongsan 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 Shinhan Inverse and Poongsan into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Shinhan Inverse WTI and Poongsan, you can compare the effects of market volatilities on Shinhan Inverse and Poongsan 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 Shinhan Inverse with a short position of Poongsan. Check out your portfolio center. Please also check ongoing floating volatility patterns of Shinhan Inverse and Poongsan.
Diversification Opportunities for Shinhan Inverse and Poongsan
0.26 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Shinhan and Poongsan is 0.26. Overlapping area represents the amount of risk that can be diversified away by holding Shinhan Inverse WTI and Poongsan in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Poongsan and Shinhan Inverse 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 Shinhan Inverse WTI are associated (or correlated) with Poongsan. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Poongsan has no effect on the direction of Shinhan Inverse i.e., Shinhan Inverse and Poongsan go up and down completely randomly.
Pair Corralation between Shinhan Inverse and Poongsan
Assuming the 90 days trading horizon Shinhan Inverse WTI is expected to under-perform the Poongsan. But the stock apears to be less risky and, when comparing its historical volatility, Shinhan Inverse WTI is 1.3 times less risky than Poongsan. The stock trades about -0.3 of its potential returns per unit of risk. The Poongsan is currently generating about 0.17 of returns per unit of risk over similar time horizon. If you would invest 5,210,000 in Poongsan on October 25, 2024 and sell it today you would earn a total of 350,000 from holding Poongsan or generate 6.72% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Shinhan Inverse WTI vs. Poongsan
Performance |
| Timeline |
| Shinhan Inverse WTI |
| Poongsan |
Shinhan Inverse and Poongsan Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Shinhan Inverse and Poongsan
The main advantage of trading using opposite Shinhan Inverse and Poongsan positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Shinhan Inverse position performs unexpectedly, Poongsan 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 Poongsan will offset losses from the drop in Poongsan's long position.| Shinhan Inverse vs. KB Financial Group | Shinhan Inverse vs. Shinhan Financial Group | Shinhan Inverse vs. Hana Financial | Shinhan Inverse vs. Woori Financial Group |
| Poongsan vs. Seers Technology | Poongsan vs. AeroSpace Technology of | Poongsan vs. Adaptive Plasma Technology | Poongsan vs. Orbitech Co |
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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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