Correlation Between Korea Computer and Lotte Data
Can any of the company-specific risk be diversified away by investing in both Korea Computer and Lotte Data 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 Computer and Lotte Data into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Korea Computer and Lotte Data Communication, you can compare the effects of market volatilities on Korea Computer and Lotte Data 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 Computer with a short position of Lotte Data. Check out your portfolio center. Please also check ongoing floating volatility patterns of Korea Computer and Lotte Data.
Diversification Opportunities for Korea Computer and Lotte Data
0.71 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Korea and Lotte is 0.71. Overlapping area represents the amount of risk that can be diversified away by holding Korea Computer and Lotte Data Communication in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Lotte Data Communication and Korea Computer 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 Computer are associated (or correlated) with Lotte Data. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Lotte Data Communication has no effect on the direction of Korea Computer i.e., Korea Computer and Lotte Data go up and down completely randomly.
Pair Corralation between Korea Computer and Lotte Data
Assuming the 90 days trading horizon Korea Computer is expected to generate 0.93 times more return on investment than Lotte Data. However, Korea Computer is 1.08 times less risky than Lotte Data. It trades about 0.03 of its potential returns per unit of risk. Lotte Data Communication is currently generating about -0.01 per unit of risk. If you would invest 422,126 in Korea Computer on September 4, 2024 and sell it today you would earn a total of 65,374 from holding Korea Computer or generate 15.49% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Korea Computer vs. Lotte Data Communication
Performance |
| Timeline |
| Korea Computer |
| Lotte Data Communication |
Korea Computer and Lotte Data Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Korea Computer and Lotte Data
The main advantage of trading using opposite Korea Computer and Lotte Data positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Korea Computer position performs unexpectedly, Lotte Data 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 Lotte Data will offset losses from the drop in Lotte Data's long position.| Korea Computer vs. Aprogen Healthcare Games | Korea Computer vs. Daol Investment Securities | Korea Computer vs. Seoul Semiconductor Co | Korea Computer vs. Korea Investment Holdings |
| Lotte Data vs. SK Holdings Co | Lotte Data vs. ASTORY CoLtd | Lotte Data vs. Industrial Bank | Lotte Data vs. AnterogenCoLtd |
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 Portfolio Backtesting module to avoid under-diversification and over-optimization by backtesting your portfolios.
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