Correlation Between Samsung Life and Total Soft
Can any of the company-specific risk be diversified away by investing in both Samsung Life and Total Soft 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 Total Soft 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 Total Soft Bank, you can compare the effects of market volatilities on Samsung Life and Total Soft 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 Total Soft. Check out your portfolio center. Please also check ongoing floating volatility patterns of Samsung Life and Total Soft.
Diversification Opportunities for Samsung Life and Total Soft
0.2 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Samsung and Total is 0.2. Overlapping area represents the amount of risk that can be diversified away by holding Samsung Life Insurance and Total Soft Bank in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Total Soft Bank 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 Total Soft. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Total Soft Bank has no effect on the direction of Samsung Life i.e., Samsung Life and Total Soft go up and down completely randomly.
Pair Corralation between Samsung Life and Total Soft
Assuming the 90 days trading horizon Samsung Life is expected to generate 2.94 times less return on investment than Total Soft. But when comparing it to its historical volatility, Samsung Life Insurance is 2.26 times less risky than Total Soft. It trades about 0.04 of its potential returns per unit of risk. Total Soft Bank is currently generating about 0.06 of returns per unit of risk over similar time horizon. If you would invest 510,000 in Total Soft Bank on August 28, 2024 and sell it today you would earn a total of 20,000 from holding Total Soft Bank or generate 3.92% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Weak |
| Accuracy | 100.0% |
| Values | Daily Returns |
Samsung Life Insurance vs. Total Soft Bank
Performance |
| Timeline |
| Samsung Life Insurance |
| Total Soft Bank |
Samsung Life and Total Soft Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Samsung Life and Total Soft
The main advantage of trading using opposite Samsung Life and Total Soft positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Samsung Life position performs unexpectedly, Total Soft 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 Total Soft will offset losses from the drop in Total Soft's long position.| Samsung Life vs. AptaBio Therapeutics | Samsung Life vs. Daewoo SBI SPAC | Samsung Life vs. Dream Security co | Samsung Life vs. Microfriend |
| Total Soft vs. Posco ICT | Total Soft vs. Devsisters corporation | Total Soft vs. Nice Information Telecommunication | Total Soft vs. InfoBank |
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 Performance Analysis module to check effects of mean-variance optimization against your current asset allocation.
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