BMO Equal Etf Forward View - Polynomial Regression
| ZUB Etf | CAD 36.02 0.22 0.61% |
BMO Equal's Polynomial Regression reference data reflects the model's output when applied to available daily price observations. This page summarizes the model output and key accuracy metrics for reference. The projected value and error metrics are calculated from available daily price observations.
The Polynomial Regression forecasted value of BMO Equal Weight on the next trading day is expected to be 33.89 with a mean absolute deviation of 0.84 and the sum of the absolute errors of 52.14.A single variable polynomial regression model attempts to put a curve through the BMO Equal historical price points. Mathematically, assuming the independent variable is X and the dependent variable is Y, this line can be indicated as: Y = a0 + a1*X + a2*X2 + a3*X3 + ... + am*Xm The Polynomial Regression reference values for BMO Equal are derived from publicly available price data and should be used for informational purposes only. Polynomial Regression Price Forecast For the 27th of March
Given 90 days horizon, the Polynomial Regression forecasted value of BMO Equal Weight on the next trading day is expected to be 33.89 with a mean absolute deviation of 0.84 , mean absolute percentage error of 0.98 , and the sum of the absolute errors of 52.14 .Please note that although there have been many attempts to predict BMO Etf prices using its time series forecasting, we generally do not suggest using it to place bets in the real market. The most commonly used models for forecasting predictions are the autoregressive models, which specify that BMO Equal's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Etf Forecast Pattern
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Forecasted Value
Forecasting BMO Equal Weight for the next session involves measuring the model's historical ability to define credible downside and upside scenarios. The projected forecast band currently runs from roughly 32.41 on the downside to about 35.36 on the upside.
Model Predictive Factors
The below table displays some essential indicators generated by the model showing the Polynomial Regression forecasting method's relative quality and the estimations of the prediction error of BMO Equal etf data series using in forecasting. Note that when a statistical model is used to represent BMO Equal etf, the representation will rarely be exact; so some information will be lost using the model to explain the process. AIC estimates the relative amount of information lost by a given model: the less information a model loses, the higher its quality.| AIC | Akaike Information Criteria | 119.933 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.8409 |
| MAPE | Mean absolute percentage error | 0.0221 |
| SAE | Sum of the absolute errors | 52.1359 |
Other Forecasting Options for BMO Equal
Relative Strength Index values for BMO measure the speed and magnitude of recent price changes. Recognizing these clusters in BMO Equal's returns helps calibrate position size and stop-loss levels. Candlestick pattern analysis of BMO Etf daily data can reveal short-term reversal or continuation signals.BMO Equal Related Equities
These stocks are related to BMO Equal within the Financial Services Equity space and can be used for peer review, pricing, or spreading risk. Return on equity across these peers shows how well each firm turns capital into profit. Falling behind peers on key ratios may signal headwinds or execution issues worth looking into.
| Risk & Return | Correlation |
BMO Equal Market Strength Events
Market strength indicators provide a structured view of how BMO Equal etf is positioned relative to trends. These indicators are valuable tools for identifying when to enter or exit positions in BMO Equal Weight. These signals help validate or refine position timing for BMO Equal.
BMO Equal Risk Indicators
The analysis of BMO Equal's risk metrics is one of the most important steps in projecting its future price. This process quantifies the risk associated with BMO Equal's and helps determine how to manage it. A structured analysis of BMO Equal's risk indicators is one of the most reliable ways to improve forecast accuracy.
| Mean Deviation | 1.11 | |||
| Standard Deviation | 1.44 | |||
| Variance | 2.06 |
Please note, the risk measures we provide can be used independently or collectively to perform a risk assessment. When comparing two potential investments, we recommend comparing similar equities with homogenous growth potential and valuation from related markets to determine which investment holds the most risk.
Story Coverage note for BMO Equal
A coverage review of BMO Equal Weight shows when the security is attracting above-average attention from contributors and market observers. The practical risk is that faster visibility can increase both interest and skepticism at the same time.
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The ratio set for BMO Equal connects key financial figures across reports. This helps frame how profit and cash flow relate to overall value.