Correlation Between Shinhan Inverse and LS Materials
Can any of the company-specific risk be diversified away by investing in both Shinhan Inverse and LS Materials 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 LS Materials 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 LS Materials, you can compare the effects of market volatilities on Shinhan Inverse and LS Materials 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 LS Materials. Check out your portfolio center. Please also check ongoing floating volatility patterns of Shinhan Inverse and LS Materials.
Diversification Opportunities for Shinhan Inverse and LS Materials
-0.86 | Correlation Coefficient |
Pay attention - limited upside
The 3 months correlation between Shinhan and 417200 is -0.86. Overlapping area represents the amount of risk that can be diversified away by holding Shinhan Inverse Copper and LS Materials in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on LS Materials 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 LS Materials. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of LS Materials has no effect on the direction of Shinhan Inverse i.e., Shinhan Inverse and LS Materials go up and down completely randomly.
Pair Corralation between Shinhan Inverse and LS Materials
Assuming the 90 days trading horizon Shinhan Inverse Copper is expected to generate 0.37 times more return on investment than LS Materials. However, Shinhan Inverse Copper is 2.69 times less risky than LS Materials. It trades about 0.12 of its potential returns per unit of risk. LS Materials is currently generating about -0.19 per unit of risk. If you would invest 526,000 in Shinhan Inverse Copper on October 9, 2024 and sell it today you would earn a total of 40,000 from holding Shinhan Inverse Copper or generate 7.6% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Significant |
Accuracy | 91.8% |
Values | Daily Returns |
Shinhan Inverse Copper vs. LS Materials
Performance |
Timeline |
Shinhan Inverse Copper |
LS Materials |
Shinhan Inverse and LS Materials Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Shinhan Inverse and LS Materials
The main advantage of trading using opposite Shinhan Inverse and LS Materials positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Shinhan Inverse position performs unexpectedly, LS Materials 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 LS Materials will offset losses from the drop in LS Materials' long position.Shinhan Inverse vs. AptaBio Therapeutics | Shinhan Inverse vs. Daewoo SBI SPAC | Shinhan Inverse vs. Dream Security co | Shinhan Inverse vs. Microfriend |
LS Materials vs. Samsung Electronics Co | LS Materials vs. Samsung Electronics Co | LS Materials vs. LG Energy Solution | LS Materials vs. SK Hynix |
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 Price Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
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