Correlation Between Samsung Life and Busan Ind
Can any of the company-specific risk be diversified away by investing in both Samsung Life and Busan Ind 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 Busan Ind 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 Busan Ind, you can compare the effects of market volatilities on Samsung Life and Busan Ind 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 Busan Ind. Check out your portfolio center. Please also check ongoing floating volatility patterns of Samsung Life and Busan Ind.
Diversification Opportunities for Samsung Life and Busan Ind
-0.62 | Correlation Coefficient |
Excellent diversification
The 3 months correlation between Samsung and Busan is -0.62. Overlapping area represents the amount of risk that can be diversified away by holding Samsung Life Insurance and Busan Ind in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Busan Ind 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 Busan Ind. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Busan Ind has no effect on the direction of Samsung Life i.e., Samsung Life and Busan Ind go up and down completely randomly.
Pair Corralation between Samsung Life and Busan Ind
Assuming the 90 days trading horizon Samsung Life Insurance is expected to under-perform the Busan Ind. But the stock apears to be less risky and, when comparing its historical volatility, Samsung Life Insurance is 2.23 times less risky than Busan Ind. The stock trades about -0.06 of its potential returns per unit of risk. The Busan Ind is currently generating about 0.13 of returns per unit of risk over similar time horizon. If you would invest 5,140,000 in Busan Ind on October 24, 2024 and sell it today you would earn a total of 2,940,000 from holding Busan Ind or generate 57.2% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Against |
| Strength | Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Samsung Life Insurance vs. Busan Ind
Performance |
| Timeline |
| Samsung Life Insurance |
| Busan Ind |
Samsung Life and Busan Ind Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Samsung Life and Busan Ind
The main advantage of trading using opposite Samsung Life and Busan Ind positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Samsung Life position performs unexpectedly, Busan Ind 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 Busan Ind will offset losses from the drop in Busan Ind's long position.| Samsung Life vs. ENF Technology Co | Samsung Life vs. Sajo Seafood | Samsung Life vs. Foodnamoo | Samsung Life vs. Sam Yang Foods |
| Busan Ind vs. Han Kook Steel | Busan Ind vs. DB Insurance Co | Busan Ind vs. Hankukpackage Co | Busan Ind vs. Samsung 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 Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
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