Correlation Between Samsung Life and Lotte Data
Can any of the company-specific risk be diversified away by investing in both Samsung Life 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 Samsung Life and Lotte Data into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Samsung Life Insurance and Lotte Data Communication, you can compare the effects of market volatilities on Samsung Life 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 Samsung Life with a short position of Lotte Data. Check out your portfolio center. Please also check ongoing floating volatility patterns of Samsung Life and Lotte Data.
Diversification Opportunities for Samsung Life and Lotte Data
-0.41 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Samsung and Lotte is -0.41. Overlapping area represents the amount of risk that can be diversified away by holding Samsung Life Insurance 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 Samsung Life 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 Samsung Life Insurance 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 Samsung Life i.e., Samsung Life and Lotte Data go up and down completely randomly.
Pair Corralation between Samsung Life and Lotte Data
Assuming the 90 days trading horizon Samsung Life Insurance is expected to generate 0.8 times more return on investment than Lotte Data. However, Samsung Life Insurance is 1.25 times less risky than Lotte Data. It trades about 0.04 of its potential returns per unit of risk. Lotte Data Communication is currently generating about -0.07 per unit of risk. If you would invest 8,850,000 in Samsung Life Insurance on September 30, 2024 and sell it today you would earn a total of 870,000 from holding Samsung Life Insurance or generate 9.83% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Samsung Life Insurance vs. Lotte Data Communication
Performance |
Timeline |
Samsung Life Insurance |
Lotte Data Communication |
Samsung Life and Lotte Data Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Samsung Life and Lotte Data
The main advantage of trading using opposite Samsung Life and Lotte Data positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Samsung Life 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.Samsung Life vs. AptaBio Therapeutics | Samsung Life vs. Wonbang Tech Co | Samsung Life vs. Busan Industrial Co | Samsung Life vs. Busan Ind |
Lotte Data vs. Ssangyong Information Communication | Lotte Data vs. Hyundai Green Food | Lotte Data vs. Samlip General Foods | Lotte Data vs. Seoul Electronics Telecom |
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 Correlation Analysis module to reduce portfolio risk simply by holding instruments which are not perfectly correlated.
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