SHORT-INTERMEDIATE Mutual Fund Forward View - Double Exponential Smoothing

FOSPX Fund  USD 9.05  -0.02  -0.22%   
Short Intermediate Bond Fund's Double Exponential Smoothing reference page covers the model's projected value and error measures from recent price data. The forecast output and associated deviation metrics are shown for informational use.
The Double Exponential Smoothing forecasted value of Short Intermediate Bond Fund on the next trading day is expected to be 9.05 with a mean absolute deviation of 0.01 and the sum of the absolute errors of 0.52.When Short Intermediate Bond Fund 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 Short Intermediate Bond Fund 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 SHORT-INTERMEDIATE observations are given relatively more weight in forecasting than the older observations. All Double Exponential Smoothing forecast figures shown for Short Intermediate Bond Fund are reference data reflecting model output based on available historical prices.
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 SHORT-INTERMEDIATE works best with periods where there are trends or seasonality.

Double Exponential Smoothing Price Forecast For the 27th of March

Given 90 days horizon, the Double Exponential Smoothing forecasted value of Short Intermediate Bond Fund on the next trading day is expected to be 9.05 with a mean absolute deviation of 0.01 , mean absolute percentage error of 0.0001 , and the sum of the absolute errors of 0.52 .
Please note that although there have been many attempts to predict SHORT-INTERMEDIATE 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 SHORT-INTERMEDIATE'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 Short Intermediate Bond Fund for the next session involves measuring the model's historical ability to define credible downside and upside scenarios. The current forecast range spans downside near 8.92 and upside near 9.18.
Market Value
9.05
9.05
Expected Value
9.18
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 SHORT-INTERMEDIATE mutual fund data series using in forecasting. Note that when a statistical model is used to represent SHORT-INTERMEDIATE 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 0.0011
MADMean absolute deviation0.0088
MAPEMean absolute percentage error0.001
SAESum of the absolute errors0.5192
When Short Intermediate Bond Fund 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 Short Intermediate Bond Fund 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 SHORT-INTERMEDIATE observations are given relatively more weight in forecasting than the older observations.

Other Forecasting Options for SHORT-INTERMEDIATE

Bollinger Bands applied to SHORT-INTERMEDIATE Mutual Fund price data measure how far SHORT-INTERMEDIATE has deviated from its recent average relative to its own volatility. This distinction drives the choice of forecasting model applied to SHORT-INTERMEDIATE's price data.

SHORT-INTERMEDIATE Related Equities

The peer firms below within the Short-Term Bond space can help frame SHORT-INTERMEDIATE's pricing and running costs in context. Key comparison metrics include price-to-earnings, profit margin, and revenue growth across SHORT-INTERMEDIATE's peer group. Identifying peers that steadily beat or lag SHORT-INTERMEDIATE across many periods highlights durable competitive gaps.
 Risk & Return  Correlation

SHORT-INTERMEDIATE Market Strength Events

For investors tracking Short Intermediate Bond Fund, market strength indicators offer quantitative evaluation of mutual fund behavior. These indicators add context to timing decisions around Short Intermediate Bond Fund positions.

SHORT-INTERMEDIATE Risk Indicators

Analyzing SHORT-INTERMEDIATE's basic risk indicators provides investors with a structured view of the risk-return trade-off for short-intermediate mutual fund. By identifying the level of risk embedded in SHORT-INTERMEDIATE's investment, investors can make 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 SHORT-INTERMEDIATE

The amount of media and story coverage tied to Short Intermediate Bond Fund 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.