Correlation Between Amazon and CyberAgent
Can any of the company-specific risk be diversified away by investing in both Amazon and CyberAgent 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 Amazon and CyberAgent into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Amazon Inc and CyberAgent, you can compare the effects of market volatilities on Amazon and CyberAgent 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 Amazon with a short position of CyberAgent. Check out your portfolio center. Please also check ongoing floating volatility patterns of Amazon and CyberAgent.
Diversification Opportunities for Amazon and CyberAgent
0.67 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Amazon and CyberAgent is 0.67. Overlapping area represents the amount of risk that can be diversified away by holding Amazon Inc and CyberAgent in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on CyberAgent and Amazon 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 Amazon Inc are associated (or correlated) with CyberAgent. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of CyberAgent has no effect on the direction of Amazon i.e., Amazon and CyberAgent go up and down completely randomly.
Pair Corralation between Amazon and CyberAgent
Assuming the 90 days horizon Amazon Inc is expected to generate 0.87 times more return on investment than CyberAgent. However, Amazon Inc is 1.15 times less risky than CyberAgent. It trades about 0.25 of its potential returns per unit of risk. CyberAgent is currently generating about 0.04 per unit of risk. If you would invest 16,868 in Amazon Inc on September 27, 2024 and sell it today you would earn a total of 4,772 from holding Amazon Inc or generate 28.29% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Significant |
Accuracy | 100.0% |
Values | Daily Returns |
Amazon Inc vs. CyberAgent
Performance |
Timeline |
Amazon Inc |
CyberAgent |
Amazon and CyberAgent Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Amazon and CyberAgent
The main advantage of trading using opposite Amazon and CyberAgent positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Amazon position performs unexpectedly, CyberAgent 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 CyberAgent will offset losses from the drop in CyberAgent's long position.The idea behind Amazon Inc and CyberAgent pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.CyberAgent vs. Publicis Groupe SA | CyberAgent vs. WPP PLC | CyberAgent vs. WPP PLC ADR | CyberAgent vs. JCDecaux SA |
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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