Correlation Between Insung Information and ITM Semiconductor
Can any of the company-specific risk be diversified away by investing in both Insung Information and ITM Semiconductor 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 Insung Information and ITM Semiconductor into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Insung Information Co and ITM Semiconductor Co, you can compare the effects of market volatilities on Insung Information and ITM Semiconductor 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 Insung Information with a short position of ITM Semiconductor. Check out your portfolio center. Please also check ongoing floating volatility patterns of Insung Information and ITM Semiconductor.
Diversification Opportunities for Insung Information and ITM Semiconductor
0.93 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Insung and ITM is 0.93. Overlapping area represents the amount of risk that can be diversified away by holding Insung Information Co and ITM Semiconductor Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on ITM Semiconductor and Insung Information 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 Insung Information Co are associated (or correlated) with ITM Semiconductor. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of ITM Semiconductor has no effect on the direction of Insung Information i.e., Insung Information and ITM Semiconductor go up and down completely randomly.
Pair Corralation between Insung Information and ITM Semiconductor
Assuming the 90 days trading horizon Insung Information Co is expected to generate 1.24 times more return on investment than ITM Semiconductor. However, Insung Information is 1.24 times more volatile than ITM Semiconductor Co. It trades about -0.11 of its potential returns per unit of risk. ITM Semiconductor Co is currently generating about -0.33 per unit of risk. If you would invest 224,500 in Insung Information Co on September 22, 2024 and sell it today you would lose (42,400) from holding Insung Information Co or give up 18.89% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Insung Information Co vs. ITM Semiconductor Co
Performance |
Timeline |
Insung Information |
ITM Semiconductor |
Insung Information and ITM Semiconductor Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Insung Information and ITM Semiconductor
The main advantage of trading using opposite Insung Information and ITM Semiconductor positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Insung Information position performs unexpectedly, ITM Semiconductor 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 ITM Semiconductor will offset losses from the drop in ITM Semiconductor's long position.Insung Information vs. Dongsin Engineering Construction | Insung Information vs. Doosan Fuel Cell | Insung Information vs. Daishin Balance 1 | Insung Information vs. Total Soft Bank |
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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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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