FIDELITY INCOME Mutual Fund Forward View - Triple Exponential Smoothing

FRQIX Fund  USD 56.51  -0.04  -0.07%   
The Triple Exponential Smoothing forecast shown here for FIDELITY INCOME is reference data produced from the equity's historical price series. Accuracy metrics including mean absolute deviation are provided alongside the projection.
The Triple Exponential Smoothing forecasted value of Fidelity Income Replacement on the next trading day is expected to be 56.49 with a mean absolute deviation of 0.10 and the sum of the absolute errors of 6.01.As with simple exponential smoothing, in triple exponential smoothing models past FIDELITY INCOME 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 Fidelity Income Replacement observations. This Triple Exponential Smoothing reference page for FIDELITY INCOME presents model-generated projections from historical price data for informational purposes.
Triple exponential smoothing for FIDELITY INCOME - 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 FIDELITY 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 trend in FIDELITY INCOME price movement. However, neither of these exponential smoothing models address any seasonality of Fidelity Income.

Triple Exponential Smoothing Price Forecast For the 21st of March

Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Fidelity Income Replacement on the next trading day is expected to be 56.49 with a mean absolute deviation of 0.10 , mean absolute percentage error of 0.02 , and the sum of the absolute errors of 6.01 .
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 INCOME's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Mutual Fund Forecast Pattern

Backtest FIDELITY INCOME  FIDELITY INCOME Price Prediction  Research Analysis  

Forecasted Value

The next-day forecast for Fidelity Income Replacement focuses on identifying predictive downside and upside bands that can frame a realistic trading range. At the moment, the model places downside around 56.24 and upside around 56.73 for the forecasting period.
Market Value
56.51
56.49
Expected Value
56.73
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 FIDELITY INCOME mutual fund data series using in forecasting. Note that when a statistical model is used to represent FIDELITY INCOME 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 0.0196
MADMean absolute deviation0.1001
MAPEMean absolute percentage error0.0018
SAESum of the absolute errors6.0074
As with simple exponential smoothing, in triple exponential smoothing models past FIDELITY INCOME 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 Fidelity Income Replacement observations.

Other Forecasting Options for FIDELITY INCOME

Regardless of investment experience, understanding FIDELITY INCOME's price movement is essential for anyone considering a position in FIDELITY. Price charts for FIDELITY Mutual Fund are often filled with noise that can lead to poor investment choices if not properly filtered.

FIDELITY INCOME Related Equities

The following equities are related to FIDELITY INCOME within the Target-Date 2000-2010 space and can be used for peer comparison, relative valuation, or portfolio diversification. Comparing FIDELITY INCOME 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 INCOME Market Strength Events

Market strength indicators for FIDELITY INCOME give investors insight into the mutual fund's responsiveness to broader market forces. Tracking these indicators provides context to make informed timing decisions and identify periods where trading FIDELITY INCOME is likely to be most rewarding.

FIDELITY INCOME Risk Indicators

A thorough review of FIDELITY INCOME's risk indicators is an important first step in forecasting its price and managing investment exposure. This analysis provides context for determining the appropriate level of risk to accept when holding FIDELITY INCOME's.
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 INCOME

The amount of media and story coverage tied to Fidelity Income Replacement can signal where market attention is concentrating at the moment. 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.