Correlation Between Samsung Electronics and PICKN PAY
Can any of the company-specific risk be diversified away by investing in both Samsung Electronics and PICKN PAY 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 PICKN PAY 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 PICKN PAY STORES, you can compare the effects of market volatilities on Samsung Electronics and PICKN PAY 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 PICKN PAY. Check out your portfolio center. Please also check ongoing floating volatility patterns of Samsung Electronics and PICKN PAY.
Diversification Opportunities for Samsung Electronics and PICKN PAY
-0.45 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Samsung and PICKN is -0.45. Overlapping area represents the amount of risk that can be diversified away by holding Samsung Electronics Co and PICKN PAY STORES in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on PICKN PAY STORES 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 PICKN PAY. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of PICKN PAY STORES has no effect on the direction of Samsung Electronics i.e., Samsung Electronics and PICKN PAY go up and down completely randomly.
Pair Corralation between Samsung Electronics and PICKN PAY
Assuming the 90 days trading horizon Samsung Electronics Co is expected to generate 0.81 times more return on investment than PICKN PAY. However, Samsung Electronics Co is 1.23 times less risky than PICKN PAY. It trades about 0.17 of its potential returns per unit of risk. PICKN PAY STORES is currently generating about -0.01 per unit of risk. If you would invest 70,900 in Samsung Electronics Co on April 23, 2025 and sell it today you would earn a total of 14,600 from holding Samsung Electronics Co or generate 20.59% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Samsung Electronics Co vs. PICKN PAY STORES
Performance |
Timeline |
Samsung Electronics |
PICKN PAY STORES |
Samsung Electronics and PICKN PAY Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Samsung Electronics and PICKN PAY
The main advantage of trading using opposite Samsung Electronics and PICKN PAY positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Samsung Electronics position performs unexpectedly, PICKN PAY 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 PICKN PAY will offset losses from the drop in PICKN PAY's long position.Samsung Electronics vs. Pentair plc | Samsung Electronics vs. GEAR4MUSIC LS 10 | Samsung Electronics vs. SWISS WATER DECAFFCOFFEE | Samsung Electronics vs. Alaska Air 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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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