Stocksplus Mutual Fund Forward View - Simple Exponential Smoothing

PSTIX Fund  USD 6.94  0.10  1.46%   
The Simple Exponential Smoothing forecast shown here for Stocksplus is reference data produced from its historical price series. The projected value and error measures below serve as reference information. This data is provided for reference and analytical review. The Simple Exponential Smoothing output serves as one input among many for analytical review.
The Simple Exponential Smoothing forecasted value of Stocksplus Tr Short on the next trading day is expected to be 6.94 with a mean absolute deviation of 0.04 and the sum of the absolute errors of 2.26.This simple exponential smoothing model begins by setting Stocksplus Tr Short forecast for the second period equal to the observation of the first period. In other words, recent Stocksplus observations are given relatively more weight in forecasting than the older observations. This Simple Exponential Smoothing reference page for Stocksplus presents model-generated projections from historical price data for informational purposes.
Stocksplus simple exponential smoothing forecast is a very popular model used to produce a smoothed price series. Whereas in simple Moving Average models the past observations for Stocksplus Tr Short are weighted equally, Exponential Smoothing assigns exponentially decreasing weights as Stocksplus Tr Short prices get older.

Simple Exponential Smoothing Price Forecast For the 24th of March

Given 90 days horizon, the Simple Exponential Smoothing forecasted value of Stocksplus Tr Short on the next trading day is expected to be 6.94 with a mean absolute deviation of 0.04 , mean absolute percentage error of 0.0023 , and the sum of the absolute errors of 2.26 .
Please note that although there have been many attempts to predict Stocksplus 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 Stocksplus' 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

For the next trading day, Macroaxis evaluates Stocksplus' predictive range by looking for statistically meaningful downside and upside boundaries. At the moment, the model places downside around 6.21 and upside around 7.67 for the forecasting period.
Market Value
6.94
6.94
Expected Value
7.67
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Simple Exponential Smoothing forecasting method's relative quality and the estimations of the prediction error of Stocksplus mutual fund data series using in forecasting. Note that when a statistical model is used to represent Stocksplus 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 Criteria110.2156
BiasArithmetic mean of the errors -0.0089
MADMean absolute deviation0.0377
MAPEMean absolute percentage error0.0057
SAESum of the absolute errors2.2599
This simple exponential smoothing model begins by setting Stocksplus Tr Short forecast for the second period equal to the observation of the first period. In other words, recent Stocksplus observations are given relatively more weight in forecasting than the older observations.

Other Forecasting Options for Stocksplus

The distribution of Stocksplus' daily returns is typically non-normal, with fatter tails than a Gaussian model predicts. This can reveal hidden support and resistance zones in Stocksplus' chart that simple price charts miss. The slope of Stocksplus' linear regression channel quantifies trend direction and strength over a chosen lookback period. Divergences between OBV and price can foreshadow trend changes in Stocksplus.

Stocksplus Related Equities

The peer firms below within the Trading--Inverse Equity space can help frame Stocksplus' pricing and running costs in context. Key comparison metrics include price-to-earnings, profit margin, and revenue growth across Stocksplus' peer group. Investors should look for peers that steadily beat or lag Stocksplus across many periods.
 Risk & Return  Correlation

Stocksplus Market Strength Events

Market strength indicators for Stocksplus give insight into the mutual fund's responsiveness to broader forces. These indicators are useful for traders seeking optimal timing for positions in Stocksplus Tr Short. Market strength analysis for Stocksplus Tr Short works best when combined with volume and volatility data. For Stocksplus, strength indicators are a practical complement to price and fundamental analysis.

Stocksplus Risk Indicators

A thorough review of Stocksplus' risk indicators is an important first step in forecasting its price. Quantifying the risk involved in Stocksplus' allows investors to make better decisions about entry, sizing, and hedging. The assessment of Stocksplus' risk indicators plays a key role in managing investment exposure. Identifying the magnitude of risk in Stocksplus' provides context to choose between accepting or hedging exposure.
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 Stocksplus

The amount of media and story coverage tied to Stocksplus Tr Short can signal where market attention is concentrating at the moment. This is most useful when investors want to understand why a security is suddenly drawing more public discussion.

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.