Fidelity Sai Mutual Fund Forward View - Triple Exponential Smoothing

FSPWX Fund   10.10  -0.08  -0.79%   
This page provides Triple Exponential Smoothing reference data for Fidelity Sai Inflation Protected, calculated from historical daily prices. The model output shown here is derived from Fidelity Sai's historical price series and is provided for informational purposes. Projected values and accuracy measures are included for reference.
The Triple Exponential Smoothing forecasted value of Fidelity Sai Inflation Protected on the next trading day is expected to be 10.09 with a mean absolute deviation of 0.02 and the sum of the absolute errors of 1.02.As with simple exponential smoothing, in triple exponential smoothing models past Fidelity Sai 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 Sai Inflation Protected observations. The Triple Exponential Smoothing reference information for Fidelity Sai is based on available price data and is intended for informational purposes.
Triple exponential smoothing for Fidelity Sai - 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 Sai 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 Sai price movement. However, neither of these exponential smoothing models address any seasonality of Fidelity Sai Inflation.

Triple Exponential Smoothing Price Forecast For the 24th of March

Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Fidelity Sai Inflation Protected on the next trading day is expected to be 10.09 with a mean absolute deviation of 0.02 , mean absolute percentage error of 0.0005 , and the sum of the absolute errors of 1.02 .
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 Sai'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

For the next trading day, Macroaxis evaluates Fidelity Sai's predictive range by looking for statistically meaningful downside and upside boundaries. The projected forecast band currently runs from roughly 9.89 on the downside to about 10.28 on the upside.
Market Value
10.10
10.09
Expected Value
10.28
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 Sai mutual fund data series using in forecasting. Note that when a statistical model is used to represent Fidelity Sai 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 0.0045
MADMean absolute deviation0.0173
MAPEMean absolute percentage error0.0017
SAESum of the absolute errors1.0219
As with simple exponential smoothing, in triple exponential smoothing models past Fidelity Sai 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 Sai Inflation Protected observations.

Other Forecasting Options for Fidelity Sai

The autocorrelation structure of Fidelity Sai's daily returns reveals whether Fidelity exhibits momentum, mean-reversion, or random-walk behavior. Separating these elements helps distinguish persistent directional moves from temporary noise in Fidelity Mutual Fund price data. Stochastic oscillator analysis compares Fidelity Sai's closing price to its range over a given period.

Fidelity Sai Related Equities

Investors studying Fidelity Sai often look at related stocks within the Inflation-Protected Bond space to gauge pricing and results. Return on equity across these peers shows how well each firm turns capital into profit. Firms that trade at big discounts to peers on core metrics may be worth more research.
 Risk & Return  Correlation

Fidelity Sai Market Strength Events

Market strength indicators applied to Fidelity Sai mutual fund help assess momentum and resilience across environments. Investors can use these indicators to make informed decisions about market timing when trading Fidelity Sai. For Fidelity Sai Inflation Protected, market strength indicators complement fundamental analysis with timing context.

Fidelity Sai Risk Indicators

Risk indicator analysis for Fidelity Sai is essential for accurately projecting its future price trajectory. The process involves identifying the amount of risk involved in Fidelity Sai's investment and either accepting or mitigating it. Understanding the risk profile of Fidelity Sai's allows investors to make more informed decisions about position sizing.
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 Sai

The amount of media and story coverage tied to Fidelity Sai Inflation Protected 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 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.