PACIFIC FUNDS Mutual Fund Forward View - Triple Exponential Smoothing

PLIDX Fund  USD 9.73  0.02  0.21%   
The Triple Exponential Smoothing forecast reference data for Pacific Funds E is based on the equity's recent trading history. This page summarizes the model output and key accuracy metrics for reference.
The Triple Exponential Smoothing forecasted value of Pacific Funds E on the next trading day is expected to be 9.73 with a mean absolute deviation of 0.02 and the sum of the absolute errors of 0.94.As with simple exponential smoothing, in triple exponential smoothing models past PACIFIC FUNDS 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 Pacific Funds E observations. All Triple Exponential Smoothing forecast figures shown for Pacific Funds E are reference data reflecting model output based on available historical prices.
Triple exponential smoothing for PACIFIC FUNDS - 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 PACIFIC FUNDS 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 PACIFIC FUNDS price movement. However, neither of these exponential smoothing models address any seasonality of Pacific Funds E.

Triple Exponential Smoothing Price Forecast For the 19th of March

Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Pacific Funds E on the next trading day is expected to be 9.73 with a mean absolute deviation of 0.02 , mean absolute percentage error of 0.0004 , and the sum of the absolute errors of 0.94 .
Please note that although there have been many attempts to predict PACIFIC 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 PACIFIC FUNDS'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 Pacific Funds E uses model performance to estimate practical downside and upside boundaries rather than a single point target alone. The projected forecast band currently runs from roughly 9.53 on the downside to about 9.92 on the upside.
Market Value
9.73
9.73
Expected Value
9.92
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 PACIFIC FUNDS mutual fund data series using in forecasting. Note that when a statistical model is used to represent PACIFIC FUNDS 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 0.0031
MADMean absolute deviation0.0157
MAPEMean absolute percentage error0.0016
SAESum of the absolute errors0.9411
As with simple exponential smoothing, in triple exponential smoothing models past PACIFIC FUNDS 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 Pacific Funds E observations.

Other Forecasting Options for PACIFIC FUNDS

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

PACIFIC FUNDS Related Equities

The following equities are related to PACIFIC FUNDS within the Intermediate Core-Plus Bond space and can be used for peer comparison, relative valuation, or portfolio diversification. Comparing PACIFIC FUNDS 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

PACIFIC FUNDS Market Strength Events

Analyzing market strength indicators for PACIFIC FUNDS 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 Pacific Funds E.

PACIFIC FUNDS Risk Indicators

Identifying and analyzing PACIFIC FUNDS's key risk indicators is a foundational step in projecting how its price may evolve. This process helps investors quantify the risk associated with PACIFIC FUNDS'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 PACIFIC FUNDS

Story coverage around Pacific Funds E often expands when market conditions, narrative momentum, or risk-adjusted performance make the security more visible to investors. A disciplined read of coverage helps investors separate durable relevance from temporary noise.

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.