Correlation Between DB Insurance and Lotte Data
Can any of the company-specific risk be diversified away by investing in both DB Insurance 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 DB Insurance and Lotte Data into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between DB Insurance Co and Lotte Data Communication, you can compare the effects of market volatilities on DB Insurance 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 DB Insurance with a short position of Lotte Data. Check out your portfolio center. Please also check ongoing floating volatility patterns of DB Insurance and Lotte Data.
Diversification Opportunities for DB Insurance and Lotte Data
0.53 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between 005830 and Lotte is 0.53. Overlapping area represents the amount of risk that can be diversified away by holding DB Insurance Co 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 DB Insurance 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 DB Insurance Co 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 DB Insurance i.e., DB Insurance and Lotte Data go up and down completely randomly.
Pair Corralation between DB Insurance and Lotte Data
Assuming the 90 days trading horizon DB Insurance Co is expected to under-perform the Lotte Data. In addition to that, DB Insurance is 1.47 times more volatile than Lotte Data Communication. It trades about -0.09 of its total potential returns per unit of risk. Lotte Data Communication is currently generating about 0.03 per unit of volatility. If you would invest 1,940,000 in Lotte Data Communication on November 3, 2024 and sell it today you would earn a total of 14,000 from holding Lotte Data Communication or generate 0.72% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
DB Insurance Co vs. Lotte Data Communication
Performance |
| Timeline |
| DB Insurance |
| Lotte Data Communication |
DB Insurance and Lotte Data Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with DB Insurance and Lotte Data
The main advantage of trading using opposite DB Insurance and Lotte Data positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if DB Insurance 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.| DB Insurance vs. Puloon Technology | DB Insurance vs. Koryo Credit Information | DB Insurance vs. PH Tech Co | DB Insurance vs. Jeju Bank |
| Lotte Data vs. Daishin Information Communications | Lotte Data vs. Nable Communications | Lotte Data vs. Korea Information Communications | Lotte Data vs. Coloray International Investment |
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 Transformation module to use Price Transformation models to analyze the depth of different equity instruments across global markets.
Other Complementary Tools
| Portfolio Dashboard Portfolio dashboard that provides centralized access to all your investments | |
| Equity Analysis Research over 250,000 global equities including funds, stocks and ETFs to find investment opportunities | |
| Price Ceiling Movement Calculate and plot Price Ceiling Movement for different equity instruments | |
| FinTech Suite Use AI to screen and filter profitable investment opportunities | |
| Portfolio Center All portfolio management and optimization tools to improve performance of your portfolios |