Correlation Between AGF Management and Sienna Resources
Can any of the company-specific risk be diversified away by investing in both AGF Management and Sienna Resources 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 AGF Management and Sienna Resources into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between AGF Management Limited and Sienna Resources, you can compare the effects of market volatilities on AGF Management and Sienna Resources 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 AGF Management with a short position of Sienna Resources. Check out your portfolio center. Please also check ongoing floating volatility patterns of AGF Management and Sienna Resources.
Diversification Opportunities for AGF Management and Sienna Resources
-0.5 | Correlation Coefficient |
Very good diversification
The 3 months correlation between AGF and Sienna is -0.5. Overlapping area represents the amount of risk that can be diversified away by holding AGF Management Limited and Sienna Resources in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Sienna Resources and AGF Management 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 AGF Management Limited are associated (or correlated) with Sienna Resources. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Sienna Resources has no effect on the direction of AGF Management i.e., AGF Management and Sienna Resources go up and down completely randomly.
Pair Corralation between AGF Management and Sienna Resources
Assuming the 90 days trading horizon AGF Management is expected to generate 5.05 times less return on investment than Sienna Resources. But when comparing it to its historical volatility, AGF Management Limited is 6.42 times less risky than Sienna Resources. It trades about 0.07 of its potential returns per unit of risk. Sienna Resources is currently generating about 0.05 of returns per unit of risk over similar time horizon. If you would invest 4.00 in Sienna Resources on September 28, 2024 and sell it today you would earn a total of 0.00 from holding Sienna Resources or generate 0.0% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Against |
Strength | Very Weak |
Accuracy | 100.0% |
Values | Daily Returns |
AGF Management Limited vs. Sienna Resources
Performance |
Timeline |
AGF Management |
Sienna Resources |
AGF Management and Sienna Resources Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with AGF Management and Sienna Resources
The main advantage of trading using opposite AGF Management and Sienna Resources positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if AGF Management position performs unexpectedly, Sienna Resources 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 Sienna Resources will offset losses from the drop in Sienna Resources' long position.AGF Management vs. IGM Financial | AGF Management vs. CI Financial Corp | AGF Management vs. iA Financial | AGF Management vs. Transcontinental |
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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 Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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