Correlation Between Samsung Electronics and Athelney Trust
Can any of the company-specific risk be diversified away by investing in both Samsung Electronics and Athelney Trust 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 Athelney Trust 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 Athelney Trust plc, you can compare the effects of market volatilities on Samsung Electronics and Athelney Trust 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 Athelney Trust. Check out your portfolio center. Please also check ongoing floating volatility patterns of Samsung Electronics and Athelney Trust.
Diversification Opportunities for Samsung Electronics and Athelney Trust
0.28 | Correlation Coefficient |
Modest diversification
The 3 months correlation between Samsung and Athelney is 0.28. Overlapping area represents the amount of risk that can be diversified away by holding Samsung Electronics Co and Athelney Trust plc in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Athelney Trust plc 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 Athelney Trust. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Athelney Trust plc has no effect on the direction of Samsung Electronics i.e., Samsung Electronics and Athelney Trust go up and down completely randomly.
Pair Corralation between Samsung Electronics and Athelney Trust
Assuming the 90 days trading horizon Samsung Electronics Co is expected to under-perform the Athelney Trust. In addition to that, Samsung Electronics is 2.07 times more volatile than Athelney Trust plc. It trades about -0.14 of its total potential returns per unit of risk. Athelney Trust plc is currently generating about -0.04 per unit of volatility. If you would invest 18,000 in Athelney Trust plc on September 15, 2024 and sell it today you would lose (500.00) from holding Athelney Trust plc or give up 2.78% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
Samsung Electronics Co vs. Athelney Trust plc
Performance |
Timeline |
Samsung Electronics |
Athelney Trust plc |
Samsung Electronics and Athelney Trust Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Samsung Electronics and Athelney Trust
The main advantage of trading using opposite Samsung Electronics and Athelney Trust positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Samsung Electronics position performs unexpectedly, Athelney Trust 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 Athelney Trust will offset losses from the drop in Athelney Trust's long position.Samsung Electronics vs. Rockfire Resources plc | Samsung Electronics vs. Tlou Energy | Samsung Electronics vs. Ikigai Ventures | Samsung Electronics vs. Falcon Oil Gas |
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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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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