POPLAR FOREST Mutual Fund Forward View - Triple Exponential Smoothing

PFPFX Fund  USD 53.24  -0.55  -1.02%   
POPLAR FOREST's Triple Exponential Smoothing reference data is generated by applying the model to available daily closing prices. Accuracy metrics including mean absolute deviation are provided alongside the projection.
The Triple Exponential Smoothing forecasted value of Poplar Forest Partners on the next trading day is expected to be 53.02 with a mean absolute deviation of 0.37 and the sum of the absolute errors of 21.86.As with simple exponential smoothing, in triple exponential smoothing models past POPLAR FOREST 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 Poplar Forest Partners observations. POPLAR FOREST's Triple Exponential Smoothing reference data is provided for informational and analytical purposes and does not constitute a trading recommendation.
Triple exponential smoothing for POPLAR FOREST - 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 POPLAR FOREST 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 POPLAR FOREST price movement. However, neither of these exponential smoothing models address any seasonality of Poplar Forest Partners.

Triple Exponential Smoothing Price Forecast For the 24th of March

Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Poplar Forest Partners on the next trading day is expected to be 53.02 with a mean absolute deviation of 0.37 , mean absolute percentage error of 0.21 , and the sum of the absolute errors of 21.86 .
Please note that although there have been many attempts to predict POPLAR 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 POPLAR FOREST's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Mutual Fund Forecast Pattern

Backtest POPLAR FOREST  POPLAR FOREST Price Prediction  Research Analysis  

Forecasted Value

For the next trading day, Macroaxis evaluates POPLAR FOREST's predictive range by looking for statistically meaningful downside and upside boundaries. At the moment, the model places downside around 52.23 and upside around 53.82 for the forecasting period.
Market Value
53.24
53.02
Expected Value
53.82
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 POPLAR FOREST mutual fund data series using in forecasting. Note that when a statistical model is used to represent POPLAR FOREST 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 0.0945
MADMean absolute deviation0.3705
MAPEMean absolute percentage error0.0066
SAESum of the absolute errors21.8616
As with simple exponential smoothing, in triple exponential smoothing models past POPLAR FOREST 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 Poplar Forest Partners observations.

Other Forecasting Options for POPLAR FOREST

Analyzing POPLAR FOREST's price movement through moving averages at different time horizons reveals whether short-term momentum aligns with the longer-term trend. Touches of the upper or lower band in POPLAR FOREST's chart can signal overbought or oversold conditions.

POPLAR FOREST Related Equities

Sizing up POPLAR FOREST against these stocks within the Mid-Cap Value space shows how it compares on key financial measures. Revenue and margin checks across this group help investors set expectations for POPLAR FOREST's results. A stock that beats its peers on many metrics often deserves a closer look from value-focused investors. Peer review is one of the most widely used methods in stock research and portfolio building.
 Risk & Return  Correlation

POPLAR FOREST Market Strength Events

Market strength indicators for POPLAR FOREST mutual fund provide a framework for assessing security responsiveness. These metrics are widely used to refine market timing and identify favorable moments to trade POPLAR FOREST.

POPLAR FOREST Risk Indicators

Assessing POPLAR FOREST's risk indicators is a critical component of any rigorous approach to forecasting its future price. Forecasting POPLAR FOREST's future price accurately requires understanding and quantifying the risks present in the investment.
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 POPLAR FOREST

A coverage review of Poplar Forest Partners shows when the security is attracting above-average attention from contributors and market observers. The practical risk is that faster visibility can increase both interest and skepticism at the same time.

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.