FIDELITY FREEDOM Mutual Fund Forward View - Double Exponential Smoothing

FBIFX Fund  USD 28.12  -0.54  -1.88%   
This page provides Double Exponential Smoothing reference data for Fidelity Freedom Index, calculated from historical daily prices. The forecast output and associated deviation metrics are shown for informational use.
The Double Exponential Smoothing forecasted value of Fidelity Freedom Index on the next trading day is expected to be 28.03 with a mean absolute deviation of 0.16 and the sum of the absolute errors of 9.74.When Fidelity Freedom Index 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 Fidelity Freedom Index 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 FIDELITY FREEDOM observations are given relatively more weight in forecasting than the older observations. FIDELITY FREEDOM's Double Exponential Smoothing reference data is provided for informational and analytical purposes and does not constitute a trading recommendation.
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 FIDELITY FREEDOM 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 Fidelity Freedom Index on the next trading day is expected to be 28.03 with a mean absolute deviation of 0.16 , mean absolute percentage error of 0.04 , and the sum of the absolute errors of 9.74 .
Please note that although there have been many attempts to predict FIDELITY 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 FIDELITY FREEDOM'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

The next-day forecast for Fidelity Freedom Index focuses on identifying predictive downside and upside bands that can frame a realistic trading range. The projected forecast band currently runs from roughly 27.33 on the downside to about 28.73 on the upside.
Market Value
28.12
28.03
Expected Value
28.73
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 FIDELITY FREEDOM mutual fund data series using in forecasting. Note that when a statistical model is used to represent FIDELITY FREEDOM 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 0.0429
MADMean absolute deviation0.1623
MAPEMean absolute percentage error0.0055
SAESum of the absolute errors9.7406
When Fidelity Freedom Index 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 Fidelity Freedom Index 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 FIDELITY FREEDOM observations are given relatively more weight in forecasting than the older observations.

Other Forecasting Options for FIDELITY FREEDOM

The price movement of FIDELITY is a central concern for all potential investors, regardless of their level of expertise. FIDELITY Mutual Fund price charts can be difficult to interpret due to the noise present in the data.

FIDELITY FREEDOM Related Equities

The following equities are related to FIDELITY FREEDOM within the Target-Date 2040 space and can be used for peer comparison, relative valuation, or portfolio diversification. Comparing FIDELITY FREEDOM 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

FIDELITY FREEDOM Market Strength Events

Market strength indicators applied to FIDELITY FREEDOM mutual fund help investors assess the relative momentum and resilience of the security in different market environments. By using these indicators, traders can make more informed decisions about when to buy or sell Fidelity Freedom Index.

FIDELITY FREEDOM Risk Indicators

Risk indicator analysis for FIDELITY FREEDOM is essential for accurately projecting its future price trajectory. By identifying the level of risk embedded in FIDELITY FREEDOM's investment, investors can make informed decisions about position sizing and risk mitigation.
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 FIDELITY FREEDOM

Story coverage around Fidelity Freedom Index often expands when market conditions, narrative momentum, or risk-adjusted performance make the security more visible to investors. This is most useful when investors want to understand why a security is suddenly drawing more public discussion.

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.