Correlation Between INNOX Advanced and Seojin Automotive
Can any of the company-specific risk be diversified away by investing in both INNOX Advanced and Seojin Automotive 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 INNOX Advanced and Seojin Automotive into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between INNOX Advanced Materials and Seojin Automotive CoLtd, you can compare the effects of market volatilities on INNOX Advanced and Seojin Automotive 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 INNOX Advanced with a short position of Seojin Automotive. Check out your portfolio center. Please also check ongoing floating volatility patterns of INNOX Advanced and Seojin Automotive.
Diversification Opportunities for INNOX Advanced and Seojin Automotive
0.93 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between INNOX and Seojin is 0.93. Overlapping area represents the amount of risk that can be diversified away by holding INNOX Advanced Materials and Seojin Automotive CoLtd in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Seojin Automotive CoLtd and INNOX Advanced 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 INNOX Advanced Materials are associated (or correlated) with Seojin Automotive. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Seojin Automotive CoLtd has no effect on the direction of INNOX Advanced i.e., INNOX Advanced and Seojin Automotive go up and down completely randomly.
Pair Corralation between INNOX Advanced and Seojin Automotive
Assuming the 90 days trading horizon INNOX Advanced Materials is expected to generate 1.14 times more return on investment than Seojin Automotive. However, INNOX Advanced is 1.14 times more volatile than Seojin Automotive CoLtd. It trades about -0.1 of its potential returns per unit of risk. Seojin Automotive CoLtd is currently generating about -0.25 per unit of risk. If you would invest 2,170,000 in INNOX Advanced Materials on September 13, 2024 and sell it today you would lose (165,000) from holding INNOX Advanced Materials or give up 7.6% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
INNOX Advanced Materials vs. Seojin Automotive CoLtd
Performance |
Timeline |
INNOX Advanced Materials |
Seojin Automotive CoLtd |
INNOX Advanced and Seojin Automotive Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with INNOX Advanced and Seojin Automotive
The main advantage of trading using opposite INNOX Advanced and Seojin Automotive positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if INNOX Advanced position performs unexpectedly, Seojin Automotive 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 Seojin Automotive will offset losses from the drop in Seojin Automotive's long position.INNOX Advanced vs. SK Hynix | INNOX Advanced vs. People Technology | INNOX Advanced vs. Hana Materials | INNOX Advanced vs. SIMMTECH Co |
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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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