INFLATION PROTECTION Mutual Fund Forward View - Double Exponential Smoothing

PIPJX Fund  USD 7.17  -0.02  -0.28%   
The Double Exponential Smoothing forecast reference data for Inflation Protection Fund is based on the equity's recent trading history. Forecast values and accuracy indicators are summarized on this page for reference.
The Double Exponential Smoothing forecasted value of Inflation Protection Fund on the next trading day is expected to be 7.17 with a mean absolute deviation of 0.01 and the sum of the absolute errors of 0.72.When Inflation Protection 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 Inflation Protection 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 INFLATION PROTECTION observations are given relatively more weight in forecasting than the older observations. The Double Exponential Smoothing projections for Inflation Protection Fund are reference data based on historical daily prices and are provided as informational context.
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 INFLATION PROTECTION works best with periods where there are trends or seasonality.

Double Exponential Smoothing Price Forecast For the 28th of March

Given 90 days horizon, the Double Exponential Smoothing forecasted value of Inflation Protection Fund on the next trading day is expected to be 7.17 with a mean absolute deviation of 0.01 , mean absolute percentage error of 0.0003 , and the sum of the absolute errors of 0.72 .
Please note that although there have been many attempts to predict INFLATION 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 INFLATION PROTECTION'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 Inflation Protection Fund focuses on identifying predictive downside and upside bands that can frame a realistic trading range. The projected forecast band currently runs from roughly 6.95 on the downside to about 7.39 on the upside.
Market Value
7.17
7.17
Expected Value
7.39
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 INFLATION PROTECTION mutual fund data series using in forecasting. Note that when a statistical model is used to represent INFLATION PROTECTION 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 3.0E-4
MADMean absolute deviation0.012
MAPEMean absolute percentage error0.0017
SAESum of the absolute errors0.72
When Inflation Protection 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 Inflation Protection 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 INFLATION PROTECTION observations are given relatively more weight in forecasting than the older observations.

Other Forecasting Options for INFLATION PROTECTION

Volatility clustering is a well-documented feature of INFLATION Mutual Fund price data where periods of large moves tend to follow other large moves. When INFLATION PROTECTION's RSI reaches extreme levels, it often precedes a short-term price correction or consolidation.

INFLATION PROTECTION Related Equities

The peer firms below within the Inflation-Protected Bond space can help frame INFLATION PROTECTION's pricing and running costs in context. Growth rate gaps between INFLATION PROTECTION and its peers often explain pricing differences in the market.
 Risk & Return  Correlation

INFLATION PROTECTION Market Strength Events

Analyzing market strength indicators for INFLATION PROTECTION enables investors to understand relative mutual fund momentum. These tools help identify favorable windows for position changes in Inflation Protection Fund.

INFLATION PROTECTION Risk Indicators

Identifying and analyzing INFLATION PROTECTION's key risk indicators is a foundational step in projecting how its price may evolve. This process involves measuring the level of investment risk in INFLATION PROTECTION's and determining how best to manage 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 INFLATION PROTECTION

Coverage intensity for Inflation Protection Fund matters because narrative visibility can influence sentiment, participation, and volatility around the name. A disciplined read of coverage separates durable relevance from temporary noise.

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.