Avicanna Stock Forward View - Triple Exponential Smoothing

AVCN Stock  CAD 0.16  -0.01  -5.88%   
Avicanna's Triple Exponential Smoothing 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. This information is intended as reference material for analytical purposes.
The Triple Exponential Smoothing forecasted value of Avicanna on the next trading day is expected to be 0.15 with a mean absolute deviation of 0.01 and the sum of the absolute errors of 0.31.As with simple exponential smoothing, in triple exponential smoothing models past Avicanna observations are given exponentially smaller weights as the observations get older. In other words, recent observations are given relatively more weight in forecasting than the older Avicanna observations. The Triple Exponential Smoothing reference values for Avicanna are derived from publicly available price data and should be used for informational purposes only.
Triple exponential smoothing for Avicanna - also known as the Winters method - is a refinement of the popular double exponential smoothing model with the addition of periodicity (seasonality) component. Simple exponential smoothing technique works best with data where there are no trend or seasonality components to the data. When Avicanna prices exhibit either an increasing or decreasing trend over time, simple exponential smoothing forecasts tend to lag behind observations. Double exponential smoothing is designed to address this type of data series by taking into account any trend in Avicanna price movement. However, neither of these exponential smoothing models address any seasonality of Avicanna.

Triple Exponential Smoothing Price Forecast For the 24th of March

Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Avicanna on the next trading day is expected to be 0.15 with a mean absolute deviation of 0.01 , mean absolute percentage error of 0.000044 , and the sum of the absolute errors of 0.31 .
Please note that although there have been many attempts to predict Avicanna Stock 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 Avicanna's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Stock Forecast Pattern

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Forecasted Value

This next-day forecast for Avicanna uses model performance to estimate practical downside and upside boundaries rather than a single point target alone. Used properly, these levels provide context around forecast dispersion rather than certainty about the next closing print.
Market Value
0.16
0.0016
Downside
0.15
Expected Value
3.92
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Triple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Avicanna stock data series using in forecasting. Note that when a statistical model is used to represent Avicanna stock, 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.
AICAkaike Information CriteriaHuge
BiasArithmetic mean of the errors 4.0E-4
MADMean absolute deviation0.0053
MAPEMean absolute percentage error0.0271
SAESum of the absolute errors0.3118
As with simple exponential smoothing, in triple exponential smoothing models past Avicanna observations are given exponentially smaller weights as the observations get older. In other words, recent observations are given relatively more weight in forecasting than the older Avicanna observations.

Other Forecasting Options for Avicanna

Relative Strength Index values for Avicanna measure the speed and magnitude of recent price changes. Recognizing these clusters in Avicanna's returns helps calibrate position size and stop-loss levels. Candlestick pattern analysis of Avicanna Stock daily data can reveal short-term reversal or continuation signals. Identifying these patterns in Avicanna Stock data supports better trade timing.

Avicanna Related Equities

These stocks within the Health Care space are often compared to Avicanna by analysts and fund managers in the sector. Checking Avicanna against peers on P/E, margins, and return on equity helps put its position in context.
 Risk & Return  Correlation

Avicanna Market Strength Events

Market strength indicators provide a structured view of how Avicanna stock is positioned relative to trends. These indicators are valuable tools for identifying when to enter or exit positions in Avicanna. Investors tracking Avicanna can use these signals to validate or adjust their position timing. Review these indicators alongside Avicanna's fundamental data for a complete analytical picture.

Avicanna Risk Indicators

The analysis of Avicanna's risk metrics is one of the most important steps in projecting its future price. This process quantifies the risk associated with Avicanna's and helps determine how to manage it. A structured analysis of Avicanna's risk indicators is one of the most reliable ways to improve forecast accuracy. Investors who carefully evaluate the risks in Avicanna's are better positioned to make informed decisions.
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 Avicanna

Coverage intensity for Avicanna matters because narrative visibility can influence sentiment, participation, and volatility around the name. The stronger process compares story flow with performance, theme classification, and the level of short-term market interest.

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.

Avicanna Short Properties

Reviewing short-oriented indicators for Avicanna is useful because long and short participants often create very different signals for timing and volatility. The practical goal is to identify when the balance between long and short participation may be changing the quality of the setup.
Common Stock Shares Outstanding100 M
Cash And Short Term Investments448 K

More Resources for Avicanna Stock Analysis

Other Information on Investing in Avicanna Stock

Financial ratios highlight how financial values interact within Avicanna. All information reflects the latest available financial data and is presented for reference purposes.