Correlation Between Samsung Life and BIT Computer
Can any of the company-specific risk be diversified away by investing in both Samsung Life and BIT Computer 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 BIT Computer 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 BIT Computer Co, you can compare the effects of market volatilities on Samsung Life and BIT Computer 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 BIT Computer. Check out your portfolio center. Please also check ongoing floating volatility patterns of Samsung Life and BIT Computer.
Diversification Opportunities for Samsung Life and BIT Computer
-0.31 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Samsung and BIT is -0.31. Overlapping area represents the amount of risk that can be diversified away by holding Samsung Life Insurance and BIT Computer Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BIT Computer 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 BIT Computer. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of BIT Computer has no effect on the direction of Samsung Life i.e., Samsung Life and BIT Computer go up and down completely randomly.
Pair Corralation between Samsung Life and BIT Computer
Assuming the 90 days trading horizon Samsung Life Insurance is expected to generate 1.27 times more return on investment than BIT Computer. However, Samsung Life is 1.27 times more volatile than BIT Computer Co. It trades about 0.0 of its potential returns per unit of risk. BIT Computer Co is currently generating about -0.01 per unit of risk. If you would invest 10,040,000 in Samsung Life Insurance on September 15, 2024 and sell it today you would lose (160,000) from holding Samsung Life Insurance or give up 1.59% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Samsung Life Insurance vs. BIT Computer Co
Performance |
Timeline |
Samsung Life Insurance |
BIT Computer |
Samsung Life and BIT Computer Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Samsung Life and BIT Computer
The main advantage of trading using opposite Samsung Life and BIT Computer positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Samsung Life position performs unexpectedly, BIT Computer 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 BIT Computer will offset losses from the drop in BIT Computer's long position.Samsung Life vs. Samsung Electronics Co | Samsung Life vs. Samsung Electronics Co | Samsung Life vs. SK Hynix | Samsung Life vs. POSCO Holdings |
BIT Computer vs. Handok Clean Tech | BIT Computer vs. Youngsin Metal Industrial | BIT Computer vs. Dongil Metal Co | BIT Computer 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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