Correlation Between BMO Aggregate and AGFiQ Market
Can any of the company-specific risk be diversified away by investing in both BMO Aggregate and AGFiQ Market 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 BMO Aggregate and AGFiQ Market into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between BMO Aggregate Bond and AGFiQ Market Neutral, you can compare the effects of market volatilities on BMO Aggregate and AGFiQ Market 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 BMO Aggregate with a short position of AGFiQ Market. Check out your portfolio center. Please also check ongoing floating volatility patterns of BMO Aggregate and AGFiQ Market.
Diversification Opportunities for BMO Aggregate and AGFiQ Market
0.51 | Correlation Coefficient |
Very weak diversification
The 3 months correlation between BMO and AGFiQ is 0.51. Overlapping area represents the amount of risk that can be diversified away by holding BMO Aggregate Bond and AGFiQ Market Neutral in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on AGFiQ Market Neutral and BMO Aggregate 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 BMO Aggregate Bond are associated (or correlated) with AGFiQ Market. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of AGFiQ Market Neutral has no effect on the direction of BMO Aggregate i.e., BMO Aggregate and AGFiQ Market go up and down completely randomly.
Pair Corralation between BMO Aggregate and AGFiQ Market
Assuming the 90 days trading horizon BMO Aggregate Bond is expected to generate 0.37 times more return on investment than AGFiQ Market. However, BMO Aggregate Bond is 2.71 times less risky than AGFiQ Market. It trades about -0.18 of its potential returns per unit of risk. AGFiQ Market Neutral is currently generating about -0.14 per unit of risk. If you would invest 3,121 in BMO Aggregate Bond on September 16, 2024 and sell it today you would lose (107.00) from holding BMO Aggregate Bond or give up 3.43% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Weak |
Accuracy | 100.0% |
Values | Daily Returns |
BMO Aggregate Bond vs. AGFiQ Market Neutral
Performance |
Timeline |
BMO Aggregate Bond |
AGFiQ Market Neutral |
BMO Aggregate and AGFiQ Market Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with BMO Aggregate and AGFiQ Market
The main advantage of trading using opposite BMO Aggregate and AGFiQ Market positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if BMO Aggregate position performs unexpectedly, AGFiQ Market 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 AGFiQ Market will offset losses from the drop in AGFiQ Market's long position.BMO Aggregate vs. BMO Short Term Bond | BMO Aggregate vs. BMO Canadian Bank | BMO Aggregate vs. BMO Aggregate Bond | BMO Aggregate vs. BMO Balanced ETF |
AGFiQ Market vs. Desjardins Alt LongShort | AGFiQ Market vs. BMO Tactical Dividend | AGFiQ Market vs. NBI Liquid Alternatives | AGFiQ Market vs. BMO Premium Yield |
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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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