Correlation Between Lotte Data and Korea Shipbuilding
Can any of the company-specific risk be diversified away by investing in both Lotte Data and Korea Shipbuilding 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 Lotte Data and Korea Shipbuilding into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Lotte Data Communication and Korea Shipbuilding Offshore, you can compare the effects of market volatilities on Lotte Data and Korea Shipbuilding 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 Lotte Data with a short position of Korea Shipbuilding. Check out your portfolio center. Please also check ongoing floating volatility patterns of Lotte Data and Korea Shipbuilding.
Diversification Opportunities for Lotte Data and Korea Shipbuilding
-0.07 | Correlation Coefficient |
Good diversification
The 3 months correlation between Lotte and Korea is -0.07. Overlapping area represents the amount of risk that can be diversified away by holding Lotte Data Communication and Korea Shipbuilding Offshore in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Korea Shipbuilding and Lotte Data 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 Lotte Data Communication are associated (or correlated) with Korea Shipbuilding. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Korea Shipbuilding has no effect on the direction of Lotte Data i.e., Lotte Data and Korea Shipbuilding go up and down completely randomly.
Pair Corralation between Lotte Data and Korea Shipbuilding
Assuming the 90 days trading horizon Lotte Data Communication is expected to under-perform the Korea Shipbuilding. In addition to that, Lotte Data is 1.01 times more volatile than Korea Shipbuilding Offshore. It trades about -0.19 of its total potential returns per unit of risk. Korea Shipbuilding Offshore is currently generating about 0.06 per unit of volatility. If you would invest 19,580,000 in Korea Shipbuilding Offshore on August 25, 2024 and sell it today you would earn a total of 570,000 from holding Korea Shipbuilding Offshore or generate 2.91% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Lotte Data Communication vs. Korea Shipbuilding Offshore
Performance |
| Timeline |
| Lotte Data Communication |
| Korea Shipbuilding |
Lotte Data and Korea Shipbuilding Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Lotte Data and Korea Shipbuilding
The main advantage of trading using opposite Lotte Data and Korea Shipbuilding positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Lotte Data position performs unexpectedly, Korea Shipbuilding 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 Korea Shipbuilding will offset losses from the drop in Korea Shipbuilding's long position.| Lotte Data vs. SCI Information Service | Lotte Data vs. DataSolution | Lotte Data vs. Koryo Credit Information | Lotte Data vs. Seoul Electronics Telecom |
| Korea Shipbuilding vs. Lotte Chilsung Beverage | Korea Shipbuilding vs. Hyundai Industrial Co | Korea Shipbuilding vs. Samhwa Paint Industrial | Korea Shipbuilding vs. Seoul Food Industrial |
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 Price Exposure Probability module to analyze equity upside and downside potential for a given time horizon across multiple markets.
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