Correlation Between Amg River and City National
Can any of the company-specific risk be diversified away by investing in both Amg River and City National 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 Amg River and City National into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Amg River Road and City National Rochdale, you can compare the effects of market volatilities on Amg River and City National 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 Amg River with a short position of City National. Check out your portfolio center. Please also check ongoing floating volatility patterns of Amg River and City National.
Diversification Opportunities for Amg River and City National
0.9 | Correlation Coefficient |
Almost no diversification
The 3 months correlation between Amg and City is 0.9. Overlapping area represents the amount of risk that can be diversified away by holding Amg River Road and City National Rochdale in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on City National Rochdale and Amg River 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 Amg River Road are associated (or correlated) with City National. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of City National Rochdale has no effect on the direction of Amg River i.e., Amg River and City National go up and down completely randomly.
Pair Corralation between Amg River and City National
Assuming the 90 days horizon Amg River is expected to generate 1.17 times less return on investment than City National. In addition to that, Amg River is 1.22 times more volatile than City National Rochdale. It trades about 0.03 of its total potential returns per unit of risk. City National Rochdale is currently generating about 0.04 per unit of volatility. If you would invest 3,153 in City National Rochdale on November 29, 2024 and sell it today you would earn a total of 523.00 from holding City National Rochdale or generate 16.59% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Very Strong |
| Accuracy | 99.8% |
| Values | Daily Returns |
Amg River Road vs. City National Rochdale
Performance |
| Timeline |
| Amg River Road |
| City National Rochdale |
Amg River and City National Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Amg River and City National
The main advantage of trading using opposite Amg River and City National positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Amg River position performs unexpectedly, City National 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 City National will offset losses from the drop in City National's long position.| Amg River vs. Amg River Road | Amg River vs. Champlain Small Pany | Amg River vs. Amg River Road | Amg River vs. Marsico Global Fund |
| City National vs. T Rowe Price | City National vs. Goldman Sachs Technology | City National vs. Dreyfus Technology Growth | City National vs. Columbia Global Technology |
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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