Vanguard Commodity Mutual Fund Forward View - Double Exponential Smoothing

VCMDX Fund  USD 30.74  -0.29  -0.93%   
The Double Exponential Smoothing forecast reference data for Vanguard Commodity Strategy is based on the equity's recent trading history. This page summarizes the model output and key accuracy metrics for reference.
The Double Exponential Smoothing forecasted value of Vanguard Commodity Strategy on the next trading day is expected to be 30.84 with a mean absolute deviation of 0.27 and the sum of the absolute errors of 16.27.When Vanguard Commodity Strategy 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 Vanguard Commodity Strategy 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 Vanguard Commodity observations are given relatively more weight in forecasting than the older observations. All Double Exponential Smoothing forecast figures shown for Vanguard Commodity Strategy 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 Vanguard Commodity works best with periods where there are trends or seasonality.

Double Exponential Smoothing Price Forecast For the 21st of March

Given 90 days horizon, the Double Exponential Smoothing forecasted value of Vanguard Commodity Strategy on the next trading day is expected to be 30.84 with a mean absolute deviation of 0.27 , mean absolute percentage error of 0.14 , and the sum of the absolute errors of 16.27 .
Please note that although there have been many attempts to predict Vanguard 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 Vanguard Commodity's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Mutual Fund Forecast Pattern

Backtest Vanguard Commodity  Vanguard Commodity Price Prediction  Research Analysis  

Forecasted Value

The next-day forecast for Vanguard Commodity Strategy focuses on identifying predictive downside and upside bands that can frame a realistic trading range. At the moment, the model places downside around 29.57 and upside around 32.10 for the forecasting period.
Market Value
30.74
30.84
Expected Value
32.10
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 Vanguard Commodity mutual fund data series using in forecasting. Note that when a statistical model is used to represent Vanguard Commodity 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 0.0549
MADMean absolute deviation0.2712
MAPEMean absolute percentage error0.0096
SAESum of the absolute errors16.2727
When Vanguard Commodity Strategy 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 Vanguard Commodity Strategy 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 Vanguard Commodity observations are given relatively more weight in forecasting than the older observations.

Other Forecasting Options for Vanguard Commodity

Whether a novice or experienced investor, anyone considering Vanguard needs to understand the dynamics of Vanguard Commodity's price movement. Price charts for Vanguard Mutual Fund contain a significant amount of noise that can distort investment decisions.

Vanguard Commodity Related Equities

The following equities are related to Vanguard Commodity within the Commodities Broad Basket space and can be used for peer comparison, relative valuation, or portfolio diversification. Comparing Vanguard Commodity 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

Vanguard Commodity Market Strength Events

Analyzing market strength indicators for Vanguard Commodity enables investors to understand how the mutual fund performs relative to overall market momentum. These indicators are valuable tools for identifying when to enter or exit positions in Vanguard Commodity Strategy.

Vanguard Commodity Risk Indicators

Identifying and analyzing Vanguard Commodity's key risk indicators is a foundational step in projecting how its price may evolve. This process quantifies the risk associated with Vanguard Commodity's and decide how 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 Vanguard Commodity

A coverage review of Vanguard Commodity Strategy shows when the security is attracting above-average attention from contributors and market observers. 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.