SHORT DURATION Mutual Fund Forward View - Double Exponential Smoothing

APOAX Fund  USD 10.37  0.02  0.19%   
This reference page presents Double Exponential Smoothing forecast data for Short Duration Inflation. The model output shown here is derived from SHORT DURATION's historical price series and is provided for informational purposes.
The Double Exponential Smoothing forecasted value of Short Duration Inflation on the next trading day is expected to be 10.37 with a mean absolute deviation of 0.01 and the sum of the absolute errors of 0.48.When Short Duration Inflation 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 Duration Inflation 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 DURATION observations are given relatively more weight in forecasting than the older observations. This Double Exponential Smoothing forecast data for Short Duration Inflation is sourced from the most recent available trading data and is intended solely as reference information.
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 DURATION works best with periods where there are trends or seasonality.

Double Exponential Smoothing Price Forecast For the 19th of March

Given 90 days horizon, the Double Exponential Smoothing forecasted value of Short Duration Inflation on the next trading day is expected to be 10.37 with a mean absolute deviation of 0.01 , mean absolute percentage error of 0.000097 , and the sum of the absolute errors of 0.48 .
Please note that although there have been many attempts to predict SHORT 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 DURATION'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

This next-day forecast for Short Duration Inflation uses model performance to estimate practical downside and upside boundaries rather than a single point target alone. The current forecast range spans downside near 10.28 and upside near 10.46.
Market Value
10.37
10.37
Expected Value
10.46
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 DURATION mutual fund data series using in forecasting. Note that when a statistical model is used to represent SHORT DURATION 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 0.0013
MADMean absolute deviation0.008
MAPEMean absolute percentage error8.0E-4
SAESum of the absolute errors0.4791
When Short Duration Inflation 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 Duration Inflation 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 DURATION observations are given relatively more weight in forecasting than the older observations.

Other Forecasting Options for SHORT DURATION

For every potential investor in SHORT, whether a beginner or expert, SHORT DURATION's price movement is the inherent factor that sparks whether it is viable to invest in it or hold it better.

SHORT DURATION Related Equities

The following equities are related to SHORT DURATION within the Short-Term Inflation-Protected Bond space and can be used for peer comparison, relative valuation, or portfolio diversification. Comparing SHORT DURATION 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

SHORT DURATION Market Strength Events

Market strength indicators help investors to evaluate how SHORT DURATION mutual fund reacts to ongoing and evolving market conditions. The investors can use it to make informed decisions about market timing, and determine when trading SHORT DURATION shares will generate the highest return on.

SHORT DURATION Risk Indicators

The analysis of SHORT DURATION's basic risk indicators is one of the essential steps in accurately forecasting its future price. The process involves identifying the amount of risk involved in SHORT DURATION's investment and either accepting that risk or mitigating 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 SHORT DURATION

Story coverage around Short Duration Inflation 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.