IPower Etf Forward View - Triple Exponential Smoothing

IPW Etf  USD 1.66  -0.04  -2.35%   
This Triple Exponential Smoothing reference page for iPower Inc presents model-generated forecast data based on historical daily prices. The output values and deviation metrics are provided for informational reference.
The Triple Exponential Smoothing forecasted value of iPower Inc on the next trading day is expected to be 1.46 with a mean absolute deviation of 0.30 and the sum of the absolute errors of 18.16.As with simple exponential smoothing, in triple exponential smoothing models past IPower 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 iPower Inc observations. All Triple Exponential Smoothing forecast figures shown for iPower Inc are reference data reflecting model output based on available historical prices.
Triple exponential smoothing for IPower - 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 IPower 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 IPower price movement. However, neither of these exponential smoothing models address any seasonality of iPower Inc.

Triple Exponential Smoothing Price Forecast For the 21st of March

Given 90 days horizon, the Triple Exponential Smoothing forecasted value of iPower Inc on the next trading day is expected to be 1.46 with a mean absolute deviation of 0.30 , mean absolute percentage error of 0.17 , and the sum of the absolute errors of 18.16 .
Please note that although there have been many attempts to predict IPower 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 IPower'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

This next-day forecast for iPower Inc uses model performance to estimate practical downside and upside boundaries rather than a single point target alone. Investors should still remember that no empirical framework consistently proves that one family of forecasting models will outperform all other approaches in live markets.
Market Value
1.66
1.46
Expected Value
8.71
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 IPower etf data series using in forecasting. Note that when a statistical model is used to represent IPower 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 -0.031
MADMean absolute deviation0.3027
MAPEMean absolute percentage error0.0747
SAESum of the absolute errors18.16
As with simple exponential smoothing, in triple exponential smoothing models past IPower 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 iPower Inc observations.

Other Forecasting Options for IPower

Price movement is the most fundamental factor that determines whether IPower is a viable investment for any investor. IPower Etf price charts are often noisy, making it difficult to identify meaningful patterns without analytical tools.

IPower Related Equities

The following equities are related to IPower within the Industrials space and can be used for peer comparison, relative valuation, or portfolio diversification. Comparing IPower against peers on metrics such as P/E, margins, and return on equity helps contextualize its positioning and identify relative strengths or weaknesses.
 Risk & Return  Correlation

IPower Market Strength Events

Assessing the market strength of IPower etf provides investors with a clearer picture of how the security reacts to evolving market dynamics. These indicators can be used to identify periods when trading iPower Inc is most likely to be profitable.

IPower Risk Indicators

The analysis of IPower's basic risk metrics provides a foundation for forecasting its future price and managing investment risk. Identifying the magnitude of risk in IPower's provides context to choose between accepting or hedging 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 IPower

A coverage review of iPower Inc shows when the security is attracting above-average attention from contributors and market observers. Used properly, this context can help investors judge whether visibility is reinforcing the thesis or attracting more speculative pressure.

IPower Short Properties

A short-interest review of iPower Inc provides context for understanding whether skepticism in the market is becoming more influential. The stronger read compares short sentiment with trend behavior, volume, and the broader market narrative.
Common Stock Shares OutstandingM
Cash And Short Term InvestmentsM

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Other Information on Investing in IPower Etf

IPower financial ratios describe how key financial values relate to each other. These measures reflect profitability, cash flow, and enterprise value.