Accelerate Arbitrage Etf Forward View - Polynomial Regression
| ARB Etf | CAD 27.80 -0.16 -0.57% |
Accelerate Arbitrage'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 Accelerate Arbitrage on the next trading day is expected to be 27.98 with a mean absolute deviation of 0.08 and the sum of the absolute errors of 4.65.A single variable polynomial regression model attempts to put a curve through the Accelerate Arbitrage 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 Accelerate Arbitrage are derived from publicly available price data and should be used for informational purposes only. Polynomial Regression Price Forecast For the 25th of March
Given 90 days horizon, the Polynomial Regression forecasted value of Accelerate Arbitrage on the next trading day is expected to be 27.98 with a mean absolute deviation of 0.08 , mean absolute percentage error of 0.01 , and the sum of the absolute errors of 4.65 .Please note that although there have been many attempts to predict Accelerate 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 Accelerate Arbitrage's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).
Etf Forecast Pattern
| Backtest Accelerate Arbitrage | Accelerate Arbitrage Price Prediction | Research Analysis |
Forecasted Value
For the next trading day, Macroaxis evaluates Accelerate Arbitrage's predictive range by looking for statistically meaningful downside and upside boundaries. At the moment, the model places downside around 27.60 and upside around 28.37 for the forecasting period.
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 Accelerate Arbitrage etf data series using in forecasting. Note that when a statistical model is used to represent Accelerate Arbitrage 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 | 113.3448 |
| Bias | Arithmetic mean of the errors | None |
| MAD | Mean absolute deviation | 0.0762 |
| MAPE | Mean absolute percentage error | 0.0027 |
| SAE | Sum of the absolute errors | 4.651 |
Other Forecasting Options for Accelerate Arbitrage
Relative Strength Index values for Accelerate measure the speed and magnitude of recent price changes. Recognizing these clusters in Accelerate Arbitrage's returns helps calibrate position size and stop-loss levels. Candlestick pattern analysis of Accelerate Etf daily data can reveal short-term reversal or continuation signals.Accelerate Arbitrage Related Equities
Accelerate Arbitrage's market space within the Alternative Equity Focused space is best grasped by looking at the firms listed below. Key comparison metrics include price-to-earnings, profit margin, and revenue growth across Accelerate Arbitrage's peer group. A stock that beats its peers on many metrics often deserves a closer look from value-focused investors. The data below allows side-by-side review across the most common financial metrics.
| Risk & Return | Correlation |
Accelerate Arbitrage Market Strength Events
Market strength indicators provide a structured view of how Accelerate Arbitrage etf is positioned relative to trends. These indicators are valuable tools for identifying when to enter or exit positions in Accelerate Arbitrage. These signals help validate or refine position timing for Accelerate Arbitrage.
Accelerate Arbitrage Risk Indicators
The analysis of Accelerate Arbitrage's risk metrics is one of the most important steps in projecting its future price. This process quantifies the risk associated with Accelerate Arbitrage's and helps determine how to manage it. A structured analysis of Accelerate Arbitrage's risk indicators is one of the most reliable ways to improve forecast accuracy.
| Mean Deviation | 0.3106 | |||
| Semi Deviation | 0.4028 | |||
| Standard Deviation | 0.4307 | |||
| Variance | 0.1855 | |||
| Downside Variance | 0.2069 | |||
| Semi Variance | 0.1623 | |||
| Expected Short fall | -0.33 |
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 Accelerate Arbitrage
The amount of media and story coverage tied to Accelerate Arbitrage can signal where market attention is concentrating at the moment. This is most useful when investors want to understand why a security is suddenly drawing more public discussion.
Other Macroaxis Stories
Macroaxis story coverage is designed for a broad investing audience that ranges from self-directed traders to advisers, researchers, and institutional market participants. The content is intended to support people who want a more structured path from headline information to portfolio action.
Story Categories
Currently Trending Categories
More Resources for Accelerate Etf Analysis
Other Information on Investing in Accelerate Etf
At Accelerate Arbitrage, financial ratios outline links between core financial data. Values are aligned to support consistent measurement over time.