Correlation Between Lotte Non-Life and Han Kook
Can any of the company-specific risk be diversified away by investing in both Lotte Non-Life and Han Kook 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 Non-Life and Han Kook into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Lotte Non Life Insurance and Han Kook Steel, you can compare the effects of market volatilities on Lotte Non-Life and Han Kook 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 Non-Life with a short position of Han Kook. Check out your portfolio center. Please also check ongoing floating volatility patterns of Lotte Non-Life and Han Kook.
Diversification Opportunities for Lotte Non-Life and Han Kook
0.12 | Correlation Coefficient |
Average diversification
The 3 months correlation between Lotte and Han is 0.12. Overlapping area represents the amount of risk that can be diversified away by holding Lotte Non Life Insurance and Han Kook Steel in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Han Kook Steel and Lotte Non-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 Lotte Non Life Insurance are associated (or correlated) with Han Kook. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Han Kook Steel has no effect on the direction of Lotte Non-Life i.e., Lotte Non-Life and Han Kook go up and down completely randomly.
Pair Corralation between Lotte Non-Life and Han Kook
Assuming the 90 days trading horizon Lotte Non Life Insurance is expected to under-perform the Han Kook. But the stock apears to be less risky and, when comparing its historical volatility, Lotte Non Life Insurance is 1.69 times less risky than Han Kook. The stock trades about -0.14 of its potential returns per unit of risk. The Han Kook Steel is currently generating about 0.02 of returns per unit of risk over similar time horizon. If you would invest 197,700 in Han Kook Steel on September 23, 2024 and sell it today you would earn a total of 1,200 from holding Han Kook Steel or generate 0.61% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Lotte Non Life Insurance vs. Han Kook Steel
Performance |
Timeline |
Lotte Non Life |
Han Kook Steel |
Lotte Non-Life and Han Kook Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Lotte Non-Life and Han Kook
The main advantage of trading using opposite Lotte Non-Life and Han Kook positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Lotte Non-Life position performs unexpectedly, Han Kook 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 Han Kook will offset losses from the drop in Han Kook's long position.Lotte Non-Life vs. Polaris Office Corp | Lotte Non-Life vs. Jeju Air Co | Lotte Non-Life vs. Hanmi Semiconductor Co | Lotte Non-Life vs. Osang Healthcare Co,Ltd |
Han Kook vs. Foodnamoo | Han Kook vs. Hyundai Green Food | Han Kook vs. Samlip General Foods | Han Kook vs. Lotte Non Life Insurance |
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 Equity Valuation module to check real value of public entities based on technical and fundamental data.
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