PRINCIPAL LIFETIME Mutual Fund Forward View - Triple Exponential Smoothing

PHTFX Fund  USD 10.92  0.06  0.55%   
PRINCIPAL LIFETIME'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 Principal Lifetime Hybrid on the next trading day is expected to be 10.92 with a mean absolute deviation of 0.03 and the sum of the absolute errors of 1.79.As with simple exponential smoothing, in triple exponential smoothing models past PRINCIPAL LIFETIME 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 Principal Lifetime Hybrid observations. PRINCIPAL LIFETIME's Triple Exponential Smoothing reference data is provided for informational and analytical purposes and does not constitute a trading recommendation.
Triple exponential smoothing for PRINCIPAL LIFETIME - 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 PRINCIPAL LIFETIME 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 PRINCIPAL LIFETIME price movement. However, neither of these exponential smoothing models address any seasonality of Principal Lifetime Hybrid.

Triple Exponential Smoothing Price Forecast For the 27th of March

Given 90 days horizon, the Triple Exponential Smoothing forecasted value of Principal Lifetime Hybrid on the next trading day is expected to be 10.92 with a mean absolute deviation of 0.03 , mean absolute percentage error of 0.0017 , and the sum of the absolute errors of 1.79 .
Please note that although there have been many attempts to predict PRINCIPAL 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 PRINCIPAL LIFETIME'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 Principal Lifetime Hybrid 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 10.55 on the downside to about 11.29 on the upside.
Market Value
10.92
10.92
Expected Value
11.29
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 PRINCIPAL LIFETIME mutual fund data series using in forecasting. Note that when a statistical model is used to represent PRINCIPAL LIFETIME 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 0.0012
MADMean absolute deviation0.0298
MAPEMean absolute percentage error0.0027
SAESum of the absolute errors1.79
As with simple exponential smoothing, in triple exponential smoothing models past PRINCIPAL LIFETIME 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 Principal Lifetime Hybrid observations.

Other Forecasting Options for PRINCIPAL LIFETIME

Analyzing PRINCIPAL LIFETIME'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 PRINCIPAL LIFETIME's chart can signal overbought or oversold conditions.

PRINCIPAL LIFETIME Related Equities

Sizing up PRINCIPAL LIFETIME against these stocks within the Target-Date Retirement space shows how it compares on key financial measures. Looking at PRINCIPAL LIFETIME's pricing multiples next to these peers shows if the stock trades at a premium or discount.
 Risk & Return  Correlation

PRINCIPAL LIFETIME Market Strength Events

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

PRINCIPAL LIFETIME Risk Indicators

Assessing PRINCIPAL LIFETIME's risk indicators is a critical component of any rigorous approach to forecasting its future price. Forecasting PRINCIPAL LIFETIME'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 PRINCIPAL LIFETIME

The amount of media and story coverage tied to Principal Lifetime Hybrid can signal where market attention is concentrating at the moment. The stronger process compares story flow with performance, theme classification, and the level of short-term market interest.

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.