Harvest Tech Etf Forward View - Double Exponential Smoothing

HTA Etf  CAD 17.83  0.17  0.96%   
This reference page presents Double Exponential Smoothing forecast data for Harvest Tech Achievers. The projected values and error metrics are presented below as reference information.
The Double Exponential Smoothing forecasted value of Harvest Tech Achievers on the next trading day is expected to be 17.83 with a mean absolute deviation of 0.18 and the sum of the absolute errors of 10.55.When Harvest Tech Achievers 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 Harvest Tech Achievers trend in the prices. So in double exponential smoothing past observations are given exponentially smaller weights as the observations get older. In other words, recent Harvest Tech observations are given relatively more weight in forecasting than the older observations. This Double Exponential Smoothing forecast data for Harvest Tech Achievers is sourced from the most recent available trading data and is intended solely as reference information.
Double exponential smoothing - also known as Holt exponential smoothing is a refinement of the popular simple exponential smoothing model with an additional trending component. Double exponential smoothing model for Harvest Tech works best with periods where there are trends or seasonality.

Double Exponential Smoothing Price Forecast For the 25th of March

Given 90 days horizon, the Double Exponential Smoothing forecasted value of Harvest Tech Achievers on the next trading day is expected to be 17.83 with a mean absolute deviation of 0.18 , mean absolute percentage error of 0.05 , and the sum of the absolute errors of 10.55 .
Please note that although there have been many attempts to predict Harvest 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 Harvest Tech's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Etf Forecast Pattern

Backtest Harvest Tech  Harvest Tech Price Prediction  Research Analysis  

Forecasted Value

For the next trading day, Macroaxis evaluates Harvest Tech's predictive range by looking for statistically meaningful downside and upside boundaries. No forecasting approach has been shown to beat all others over time. Investors should treat any model output as a guide, not a guarantee.
Market Value
17.83
17.83
Expected Value
19.04
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Double Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Harvest Tech etf data series using in forecasting. Note that when a statistical model is used to represent Harvest Tech 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.
AICAkaike Information CriteriaHuge
BiasArithmetic mean of the errors 0.033
MADMean absolute deviation0.1758
MAPEMean absolute percentage error0.0096
SAESum of the absolute errors10.5501
When Harvest Tech Achievers 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 Harvest Tech Achievers trend in the prices. So in double exponential smoothing past observations are given exponentially smaller weights as the observations get older. In other words, recent Harvest Tech observations are given relatively more weight in forecasting than the older observations.

Other Forecasting Options for Harvest Tech

Harvest Tech's daily price returns can be decomposed into trend, seasonal, and residual components. Divergence between short-term and long-term averages in Harvest often signals an upcoming reversal or acceleration.

Harvest Tech Related Equities

The stocks listed below are peers of Harvest Tech within the Sector Equity space and offer context for ranking and strength. Key comparison metrics include price-to-earnings, profit margin, and revenue growth across Harvest Tech's peer group. Peer review is most useful when paired with absolute pricing and trend checks.
 Risk & Return  Correlation

Harvest Tech Market Strength Events

Market strength indicators help investors evaluate how Harvest Tech etf reacts to evolving market conditions. These indicators help determine optimal entry and exit points for trading Harvest Tech Achievers.

Harvest Tech Risk Indicators

The analysis of Harvest Tech's basic risk indicators is one of the essential steps in accurately forecasting its future price. Understanding the risk involved in holding Harvest Tech's allows investors to make informed decisions about their exposure.
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 Harvest Tech

A coverage review of Harvest Tech Achievers shows when the security is attracting above-average attention from contributors and market observers. 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.

More Resources for Harvest Etf Analysis

Other Information on Investing in Harvest Etf

Financial ratios reflect how major financial figures connect within Harvest Tech. This data is based on the latest available financial reporting cycle.