PIONEER HIGH Mutual Fund Forward View - Double Exponential Smoothing

PIMAX Fund  USD 5.59  -0.04  -0.71%   
This reference page presents Double Exponential Smoothing forecast data for Pioneer High Income. The model output shown here is derived from PIONEER HIGH's historical price series and is provided for informational purposes.
The Double Exponential Smoothing forecasted value of Pioneer High Income on the next trading day is expected to be 5.58 with a mean absolute deviation of 0.01 and the sum of the absolute errors of 0.64.When Pioneer High Income 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 Pioneer High Income 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 PIONEER HIGH observations are given relatively more weight in forecasting than the older observations. This Double Exponential Smoothing forecast data for Pioneer High Income 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 PIONEER HIGH works best with periods where there are trends or seasonality.

Double Exponential Smoothing Price Forecast For the 22nd of March

Given 90 days horizon, the Double Exponential Smoothing forecasted value of Pioneer High Income on the next trading day is expected to be 5.58 with a mean absolute deviation of 0.01 , mean absolute percentage error of 0.0002 , and the sum of the absolute errors of 0.64 .
Please note that although there have been many attempts to predict PIONEER Mutual Fund 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 PIONEER HIGH's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Mutual Fund Forecast Pattern

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Forecasted Value

Forecasting Pioneer High Income for the next session involves measuring the model's historical ability to define credible downside and upside scenarios. At the moment, the model places downside around 5.35 and upside around 5.80 for the forecasting period.
Market Value
5.59
5.58
Expected Value
5.80
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 PIONEER HIGH mutual fund data series using in forecasting. Note that when a statistical model is used to represent PIONEER HIGH mutual fund, 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 -7.0E-4
MADMean absolute deviation0.0106
MAPEMean absolute percentage error0.0019
SAESum of the absolute errors0.6385
When Pioneer High Income 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 Pioneer High Income 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 PIONEER HIGH observations are given relatively more weight in forecasting than the older observations.

Other Forecasting Options for PIONEER HIGH

For every potential investor in PIONEER, whether a beginner or expert, PIONEER HIGH's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better.

PIONEER HIGH Related Equities

The following equities are related to PIONEER HIGH within the High Yield Muni space and can be used for peer comparison, relative valuation, or portfolio diversification. Comparing PIONEER HIGH 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

PIONEER HIGH Market Strength Events

Market strength indicators help investors to evaluate how PIONEER HIGH mutual fund reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading PIONEER HIGH shares will generate the highest return on.

PIONEER HIGH Risk Indicators

The analysis of PIONEER HIGH's basic risk indicators is one of the essential steps in accurately forecasting its future price. The process involves identifying the amount of risk involved in PIONEER HIGH's investment and either accepting that risk or mitigating it.
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 PIONEER HIGH

A coverage review of Pioneer High Income 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.

Other Macroaxis Stories

Macroaxis publishes story content for a diverse readership that includes finance students, independent investors, money managers, and market-focused operating teams. What connects that audience is a focus on building stronger portfolios through better research, risk awareness, and comparative analysis.