Correlation Between Electronic Arts and RealNetworks
Can any of the company-specific risk be diversified away by investing in both Electronic Arts and RealNetworks 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 Electronic Arts and RealNetworks into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Electronic Arts and RealNetworks, you can compare the effects of market volatilities on Electronic Arts and RealNetworks 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 Electronic Arts with a short position of RealNetworks. Check out your portfolio center. Please also check ongoing floating volatility patterns of Electronic Arts and RealNetworks.
Diversification Opportunities for Electronic Arts and RealNetworks
0.62 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Electronic and RealNetworks is 0.62. Overlapping area represents the amount of risk that can be diversified away by holding Electronic Arts and RealNetworks in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on RealNetworks and Electronic Arts 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 Electronic Arts are associated (or correlated) with RealNetworks. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of RealNetworks has no effect on the direction of Electronic Arts i.e., Electronic Arts and RealNetworks go up and down completely randomly.
Pair Corralation between Electronic Arts and RealNetworks
Allowing for the 90-day total investment horizon Electronic Arts is expected to generate 0.16 times more return on investment than RealNetworks. However, Electronic Arts is 6.06 times less risky than RealNetworks. It trades about 0.02 of its potential returns per unit of risk. RealNetworks is currently generating about -0.04 per unit of risk. If you would invest 11,409 in Electronic Arts on January 26, 2024 and sell it today you would earn a total of 1,405 from holding Electronic Arts or generate 12.31% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 34.21% |
| Values | Daily Returns |
Electronic Arts vs. RealNetworks
Performance |
| Timeline |
| Electronic Arts |
| RealNetworks |
Risk-Adjusted Performance
0 of 100
Weak | Strong |
Very Weak
Electronic Arts and RealNetworks Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Electronic Arts and RealNetworks
The main advantage of trading using opposite Electronic Arts and RealNetworks positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Electronic Arts position performs unexpectedly, RealNetworks 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 RealNetworks will offset losses from the drop in RealNetworks' long position.| Electronic Arts vs. i3 Interactive | Electronic Arts vs. GameSquare Holdings | Electronic Arts vs. IGG Inc |
| RealNetworks vs. Brunswick | RealNetworks vs. Albertsons Companies | RealNetworks vs. Natural Alternatives International | RealNetworks vs. BBB Foods |
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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