Correlation Between Ainsworth Game and Aurelia Metals
Can any of the company-specific risk be diversified away by investing in both Ainsworth Game and Aurelia Metals 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 Ainsworth Game and Aurelia Metals into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Ainsworth Game Technology and Aurelia Metals, you can compare the effects of market volatilities on Ainsworth Game and Aurelia Metals 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 Ainsworth Game with a short position of Aurelia Metals. Check out your portfolio center. Please also check ongoing floating volatility patterns of Ainsworth Game and Aurelia Metals.
Diversification Opportunities for Ainsworth Game and Aurelia Metals
-0.24 | Correlation Coefficient |
Very good diversification
The 3 months correlation between Ainsworth and Aurelia is -0.24. Overlapping area represents the amount of risk that can be diversified away by holding Ainsworth Game Technology and Aurelia Metals in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Aurelia Metals and Ainsworth Game 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 Ainsworth Game Technology are associated (or correlated) with Aurelia Metals. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Aurelia Metals has no effect on the direction of Ainsworth Game i.e., Ainsworth Game and Aurelia Metals go up and down completely randomly.
Pair Corralation between Ainsworth Game and Aurelia Metals
Assuming the 90 days trading horizon Ainsworth Game Technology is expected to under-perform the Aurelia Metals. But the stock apears to be less risky and, when comparing its historical volatility, Ainsworth Game Technology is 1.6 times less risky than Aurelia Metals. The stock trades about -0.04 of its potential returns per unit of risk. The Aurelia Metals is currently generating about 0.08 of returns per unit of risk over similar time horizon. If you would invest 16.00 in Aurelia Metals on September 12, 2024 and sell it today you would earn a total of 3.00 from holding Aurelia Metals or generate 18.75% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Insignificant |
Accuracy | 100.0% |
Values | Daily Returns |
Ainsworth Game Technology vs. Aurelia Metals
Performance |
Timeline |
Ainsworth Game Technology |
Aurelia Metals |
Ainsworth Game and Aurelia Metals Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Ainsworth Game and Aurelia Metals
The main advantage of trading using opposite Ainsworth Game and Aurelia Metals positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Ainsworth Game position performs unexpectedly, Aurelia Metals 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 Aurelia Metals will offset losses from the drop in Aurelia Metals' long position.Ainsworth Game vs. COAST ENTERTAINMENT HOLDINGS | Ainsworth Game vs. Infomedia | Ainsworth Game vs. Seven West Media | Ainsworth Game vs. Retail Food 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 Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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