Correlation Between Samsung Electronics and FIRST SHIP
Can any of the company-specific risk be diversified away by investing in both Samsung Electronics and FIRST SHIP 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 Electronics and FIRST SHIP into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Samsung Electronics Co and FIRST SHIP LEASE, you can compare the effects of market volatilities on Samsung Electronics and FIRST SHIP 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 Electronics with a short position of FIRST SHIP. Check out your portfolio center. Please also check ongoing floating volatility patterns of Samsung Electronics and FIRST SHIP.
Diversification Opportunities for Samsung Electronics and FIRST SHIP
-0.18 | Correlation Coefficient |
Good diversification
The 3 months correlation between Samsung and FIRST is -0.18. Overlapping area represents the amount of risk that can be diversified away by holding Samsung Electronics Co and FIRST SHIP LEASE in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on FIRST SHIP LEASE and Samsung Electronics 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 Electronics Co are associated (or correlated) with FIRST SHIP. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of FIRST SHIP LEASE has no effect on the direction of Samsung Electronics i.e., Samsung Electronics and FIRST SHIP go up and down completely randomly.
Pair Corralation between Samsung Electronics and FIRST SHIP
Assuming the 90 days trading horizon Samsung Electronics Co is expected to under-perform the FIRST SHIP. But the stock apears to be less risky and, when comparing its historical volatility, Samsung Electronics Co is 1.68 times less risky than FIRST SHIP. The stock trades about -0.33 of its potential returns per unit of risk. The FIRST SHIP LEASE is currently generating about -0.06 of returns per unit of risk over similar time horizon. If you would invest 2.40 in FIRST SHIP LEASE on November 7, 2024 and sell it today you would lose (0.06) from holding FIRST SHIP LEASE or give up 2.5% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Samsung Electronics Co vs. FIRST SHIP LEASE
Performance |
Timeline |
Samsung Electronics |
FIRST SHIP LEASE |
Samsung Electronics and FIRST SHIP Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Samsung Electronics and FIRST SHIP
The main advantage of trading using opposite Samsung Electronics and FIRST SHIP positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Samsung Electronics position performs unexpectedly, FIRST SHIP 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 FIRST SHIP will offset losses from the drop in FIRST SHIP's long position.Samsung Electronics vs. Playa Hotels Resorts | Samsung Electronics vs. SCANSOURCE | Samsung Electronics vs. Align Technology | Samsung Electronics vs. InterContinental Hotels Group |
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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 Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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