Correlation Between Shinhan Inverse and LG Chemicals
Can any of the company-specific risk be diversified away by investing in both Shinhan Inverse and LG Chemicals 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 LG Chemicals into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Shinhan Inverse Copper and LG Chemicals, you can compare the effects of market volatilities on Shinhan Inverse and LG Chemicals 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 LG Chemicals. Check out your portfolio center. Please also check ongoing floating volatility patterns of Shinhan Inverse and LG Chemicals.
Diversification Opportunities for Shinhan Inverse and LG Chemicals
0.54 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Shinhan and 051910 is 0.54. Overlapping area represents the amount of risk that can be diversified away by holding Shinhan Inverse Copper and LG Chemicals in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on LG Chemicals 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 Copper are associated (or correlated) with LG Chemicals. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of LG Chemicals has no effect on the direction of Shinhan Inverse i.e., Shinhan Inverse and LG Chemicals go up and down completely randomly.
Pair Corralation between Shinhan Inverse and LG Chemicals
Assuming the 90 days trading horizon Shinhan Inverse Copper is expected to generate 0.57 times more return on investment than LG Chemicals. However, Shinhan Inverse Copper is 1.75 times less risky than LG Chemicals. It trades about -0.09 of its potential returns per unit of risk. LG Chemicals is currently generating about -0.1 per unit of risk. If you would invest 569,000 in Shinhan Inverse Copper on December 3, 2024 and sell it today you would lose (50,000) from holding Shinhan Inverse Copper or give up 8.79% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 96.55% |
Values | Daily Returns |
Shinhan Inverse Copper vs. LG Chemicals
Performance |
Timeline |
Shinhan Inverse Copper |
LG Chemicals |
Shinhan Inverse and LG Chemicals Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Shinhan Inverse and LG Chemicals
The main advantage of trading using opposite Shinhan Inverse and LG Chemicals positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Shinhan Inverse position performs unexpectedly, LG Chemicals 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 LG Chemicals will offset losses from the drop in LG Chemicals' long position.Shinhan Inverse vs. Hankukpackage Co | Shinhan Inverse vs. GS Retail Co | Shinhan Inverse vs. Hotel Shilla Co | Shinhan Inverse vs. Dongwoon Anatech Co |
LG Chemicals vs. Dongil Metal Co | LG Chemicals vs. Jinro Distillers Co | LG Chemicals vs. PJ Metal Co | LG Chemicals vs. Jin Air 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 Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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