VOLUMETRIC FUND Mutual Fund Forward View - Triple Exponential Smoothing

VOLMX Fund  USD 22.66  -0.18  -0.79%   
This page provides Triple Exponential Smoothing reference data for Volumetric Fund Volumetric, calculated from historical daily prices. The model output shown here is derived from VOLUMETRIC FUND's historical price series and is provided for informational purposes.
The Triple Exponential Smoothing forecasted value of Volumetric Fund Volumetric on the next trading day is expected to be 22.57 with a mean absolute deviation of 0.14 and the sum of the absolute errors of 8.04.As with simple exponential smoothing, in triple exponential smoothing models past VOLUMETRIC FUND 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 Volumetric Fund Volumetric observations. The Triple Exponential Smoothing reference information for VOLUMETRIC FUND is based on available price data and is intended for informational purposes.
Triple exponential smoothing for VOLUMETRIC FUND - 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 VOLUMETRIC 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 trend in VOLUMETRIC FUND price movement. However, neither of these exponential smoothing models address any seasonality of Volumetric Fund.

Triple Exponential Smoothing Price Forecast For the 23rd of March

Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Volumetric Fund Volumetric on the next trading day is expected to be 22.57 with a mean absolute deviation of 0.14 , mean absolute percentage error of 0.03 , and the sum of the absolute errors of 8.04 .
Please note that although there have been many attempts to predict VOLUMETRIC 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 VOLUMETRIC FUND'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 Volumetric Fund Volumetric for the next session involves measuring the model's historical ability to define credible downside and upside scenarios. The projected forecast band currently runs from roughly 21.79 on the downside to about 23.35 on the upside.
Market Value
22.66
22.57
Expected Value
23.35
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 VOLUMETRIC FUND mutual fund data series using in forecasting. Note that when a statistical model is used to represent VOLUMETRIC FUND 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 0.0367
MADMean absolute deviation0.1363
MAPEMean absolute percentage error0.0057
SAESum of the absolute errors8.0444
As with simple exponential smoothing, in triple exponential smoothing models past VOLUMETRIC FUND 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 Volumetric Fund Volumetric observations.

Other Forecasting Options for VOLUMETRIC FUND

The autocorrelation structure of VOLUMETRIC FUND's daily returns reveals whether VOLUMETRIC exhibits momentum, mean-reversion, or random-walk behavior. Separating these elements helps distinguish persistent directional moves from temporary noise in VOLUMETRIC Mutual Fund price data.

VOLUMETRIC FUND Related Equities

These related stocks within the Large Blend space give benchmarks for judging VOLUMETRIC FUND's results, margins, and growth trend. Profit comparisons show whether VOLUMETRIC FUND earns above or below average returns next to its peers. How VOLUMETRIC FUND ranks within this group can shift over time as the competitive picture changes. Tracking VOLUMETRIC FUND's results against these peers over time helps spot rising trends early.
 Risk & Return  Correlation

VOLUMETRIC FUND Market Strength Events

Market strength indicators applied to VOLUMETRIC FUND mutual fund help assess momentum and resilience across environments. Investors can use these indicators to make informed decisions about market timing when trading VOLUMETRIC FUND.

VOLUMETRIC FUND Risk Indicators

Risk indicator analysis for VOLUMETRIC FUND is essential for accurately projecting its future price trajectory. The process involves identifying the amount of risk involved in VOLUMETRIC FUND's investment and either accepting 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 VOLUMETRIC FUND

A coverage review of Volumetric Fund Volumetric shows when the security is attracting above-average attention from contributors and market observers. Used properly, this context can help investors judge whether visibility is reinforcing the thesis or attracting more speculative pressure.

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.