ROYCE PENNSYLVANIA Mutual Fund Forward View - 4 Period Moving Average

RYPFX Fund  USD 9.27  -0.15  -1.59%   
This page provides 4 Period Moving Average reference data for Royce Pennsylvania Mutual, calculated from historical daily prices. The forecast output and associated deviation metrics are shown for informational use.
The 4 Period Moving Average forecasted value of Royce Pennsylvania Mutual on the next trading day is expected to be 9.34 with a mean absolute deviation of 0.11 and the sum of the absolute errors of 6.42.The four period moving average method has an advantage over other forecasting models in that it does smooth out peaks and troughs in a set of daily price observations of ROYCE PENNSYLVANIA. However, it also has several disadvantages. In particular this model does not produce an actual prediction equation for Royce Pennsylvania Mutual and therefore, it cannot be a useful forecasting tool for medium or long range price predictions ROYCE PENNSYLVANIA's 4 Period Moving Average reference data is provided for informational and analytical purposes and does not constitute a trading recommendation.
A four-period moving average forecast model for Royce Pennsylvania Mutual is based on an artificially constructed daily price series in which the value for a given day is replaced by the mean of that value and the values for four preceding and succeeding time periods. This model is best suited to forecast equities with high volatility.

4 Period Moving Average Price Forecast For the 23rd of March

Given 90 days horizon, the 4 Period Moving Average forecasted value of Royce Pennsylvania Mutual on the next trading day is expected to be 9.34 with a mean absolute deviation of 0.11 , mean absolute percentage error of 0.02 , and the sum of the absolute errors of 6.42 .
Please note that although there have been many attempts to predict ROYCE 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 ROYCE PENNSYLVANIA'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

The next-day forecast for Royce Pennsylvania Mutual focuses on identifying predictive downside and upside bands that can frame a realistic trading range. Used properly, these levels provide context around forecast dispersion rather than certainty about the next closing print.
Market Value
9.27
9.34
Expected Value
10.44
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the 4 Period Moving Average forecasting method's relative quality and the estimations of the prediction error of ROYCE PENNSYLVANIA mutual fund data series using in forecasting. Note that when a statistical model is used to represent ROYCE PENNSYLVANIA 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 Criteria106.8318
BiasArithmetic mean of the errors 0.0025
MADMean absolute deviation0.1126
MAPEMean absolute percentage error0.0115
SAESum of the absolute errors6.42
The four period moving average method has an advantage over other forecasting models in that it does smooth out peaks and troughs in a set of daily price observations of ROYCE PENNSYLVANIA. However, it also has several disadvantages. In particular this model does not produce an actual prediction equation for Royce Pennsylvania Mutual and therefore, it cannot be a useful forecasting tool for medium or long range price predictions

Other Forecasting Options for ROYCE PENNSYLVANIA

The price movement of ROYCE is a central concern for all potential investors, regardless of their level of expertise. ROYCE Mutual Fund price charts can be difficult to interpret due to the noise present in the data.

ROYCE PENNSYLVANIA Related Equities

The following equities are related to ROYCE PENNSYLVANIA within the Small Blend space and can be used for peer comparison, relative valuation, or portfolio diversification. Comparing ROYCE PENNSYLVANIA 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

ROYCE PENNSYLVANIA Market Strength Events

Market strength indicators applied to ROYCE PENNSYLVANIA mutual fund help investors assess the relative momentum and resilience of the security in different market environments. By using these indicators, traders can make more informed decisions about when to buy or sell Royce Pennsylvania Mutual.

ROYCE PENNSYLVANIA Risk Indicators

Risk indicator analysis for ROYCE PENNSYLVANIA is essential for accurately projecting its future price trajectory. By identifying the level of risk embedded in ROYCE PENNSYLVANIA's investment, investors can make informed decisions about position sizing and risk mitigation.
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 ROYCE PENNSYLVANIA

Story coverage around Royce Pennsylvania Mutual often expands when market conditions, narrative momentum, or risk-adjusted performance make the security more visible to investors. This is most useful when investors want to understand why a security is suddenly drawing more public discussion.

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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.