Correlation Between Korea Information and Inzi Display
Can any of the company-specific risk be diversified away by investing in both Korea Information and Inzi Display 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 Korea Information and Inzi Display into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Korea Information Engineering and Inzi Display CoLtd, you can compare the effects of market volatilities on Korea Information and Inzi Display 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 Korea Information with a short position of Inzi Display. Check out your portfolio center. Please also check ongoing floating volatility patterns of Korea Information and Inzi Display.
Diversification Opportunities for Korea Information and Inzi Display
0.55 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between Korea and Inzi is 0.55. Overlapping area represents the amount of risk that can be diversified away by holding Korea Information Engineering and Inzi Display CoLtd in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Inzi Display CoLtd and Korea 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 Korea Information Engineering are associated (or correlated) with Inzi Display. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Inzi Display CoLtd has no effect on the direction of Korea Information i.e., Korea Information and Inzi Display go up and down completely randomly.
Pair Corralation between Korea Information and Inzi Display
Assuming the 90 days trading horizon Korea Information Engineering is expected to generate 1.22 times more return on investment than Inzi Display. However, Korea Information is 1.22 times more volatile than Inzi Display CoLtd. It trades about -0.3 of its potential returns per unit of risk. Inzi Display CoLtd is currently generating about -0.38 per unit of risk. If you would invest 268,500 in Korea Information Engineering on August 31, 2024 and sell it today you would lose (28,500) from holding Korea Information Engineering or give up 10.61% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Korea Information Engineering vs. Inzi Display CoLtd
Performance |
Timeline |
Korea Information |
Inzi Display CoLtd |
Korea Information and Inzi Display Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Korea Information and Inzi Display
The main advantage of trading using opposite Korea Information and Inzi Display positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Korea Information position performs unexpectedly, Inzi Display 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 Inzi Display will offset losses from the drop in Inzi Display's long position.Korea Information vs. Woorim Machinery Co | Korea Information vs. Seohee Construction Co | Korea Information vs. Pyung Hwa Industrial | Korea Information vs. Kukil Metal 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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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