Correlation Between Insung Information and CU Tech
Can any of the company-specific risk be diversified away by investing in both Insung Information and CU Tech 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 CU Tech 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 CU Tech Corp, you can compare the effects of market volatilities on Insung Information and CU Tech 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 CU Tech. Check out your portfolio center. Please also check ongoing floating volatility patterns of Insung Information and CU Tech.
Diversification Opportunities for Insung Information and CU Tech
0.87 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Insung and 376290 is 0.87. Overlapping area represents the amount of risk that can be diversified away by holding Insung Information Co and CU Tech Corp in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CU Tech Corp 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 CU Tech. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CU Tech Corp has no effect on the direction of Insung Information i.e., Insung Information and CU Tech go up and down completely randomly.
Pair Corralation between Insung Information and CU Tech
Assuming the 90 days trading horizon Insung Information Co is expected to generate 2.16 times more return on investment than CU Tech. However, Insung Information is 2.16 times more volatile than CU Tech Corp. It trades about 0.29 of its potential returns per unit of risk. CU Tech Corp is currently generating about 0.31 per unit of risk. If you would invest 161,000 in Insung Information Co on October 10, 2024 and sell it today you would earn a total of 28,300 from holding Insung Information Co or generate 17.58% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Insung Information Co vs. CU Tech Corp
Performance |
Timeline |
Insung Information |
CU Tech Corp |
Insung Information and CU Tech Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Insung Information and CU Tech
The main advantage of trading using opposite Insung Information and CU Tech positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Insung Information position performs unexpectedly, CU Tech 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 CU Tech will offset losses from the drop in CU Tech's long position.Insung Information vs. Okins Electronics Co | Insung Information vs. Korean Air Lines | Insung Information vs. Samick Musical Instruments | Insung Information vs. Daewoo Electronic Components |
CU Tech vs. Hanwha Chemical Corp | CU Tech vs. SK Chemicals Co | CU Tech vs. Hanshin Construction Co | CU Tech vs. KEPCO Engineering Construction |
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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