Correlation Between Lotte Data and Hanwha Life
Can any of the company-specific risk be diversified away by investing in both Lotte Data and Hanwha Life 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 Hanwha Life 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 Hanwha Life Insurance, you can compare the effects of market volatilities on Lotte Data and Hanwha Life 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 Hanwha Life. Check out your portfolio center. Please also check ongoing floating volatility patterns of Lotte Data and Hanwha Life.
Diversification Opportunities for Lotte Data and Hanwha Life
0.83 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Lotte and Hanwha is 0.83. Overlapping area represents the amount of risk that can be diversified away by holding Lotte Data Communication and Hanwha Life Insurance in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Hanwha Life Insurance 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 Hanwha Life. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Hanwha Life Insurance has no effect on the direction of Lotte Data i.e., Lotte Data and Hanwha Life go up and down completely randomly.
Pair Corralation between Lotte Data and Hanwha Life
Assuming the 90 days trading horizon Lotte Data Communication is expected to generate 2.37 times more return on investment than Hanwha Life. However, Lotte Data is 2.37 times more volatile than Hanwha Life Insurance. It trades about -0.01 of its potential returns per unit of risk. Hanwha Life Insurance is currently generating about -0.1 per unit of risk. If you would invest 1,977,000 in Lotte Data Communication on October 24, 2024 and sell it today you would lose (12,000) from holding Lotte Data Communication or give up 0.61% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Strong |
| Accuracy | 100.0% |
| Values | Daily Returns |
Lotte Data Communication vs. Hanwha Life Insurance
Performance |
| Timeline |
| Lotte Data Communication |
| Hanwha Life Insurance |
Lotte Data and Hanwha Life Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Lotte Data and Hanwha Life
The main advantage of trading using opposite Lotte Data and Hanwha Life positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Lotte Data position performs unexpectedly, Hanwha Life 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 Hanwha Life will offset losses from the drop in Hanwha Life's long position.| Lotte Data vs. National Plastic Co | Lotte Data vs. Phoenix Materials Co | Lotte Data vs. SCI Information Service | Lotte Data vs. Jeong Moon Information |
| Hanwha Life vs. Jin Air Co | Hanwha Life vs. DSC Investment | Hanwha Life vs. Pureun Mutual Savings | Hanwha Life vs. Daelim Trading Co |
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 USA ETFs module to find actively traded Exchange Traded Funds (ETF) in USA.
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