Applied Finance Mutual Fund Forward View - Simple Regression

AFALX Fund  USD 12.19  -0.13  -1.06%   
The Simple Regression reference data for Applied Finance is derived from the equity's published trading history. Forecast values and accuracy indicators are summarized on this page for reference.
The Simple Regression forecasted value of Applied Finance Core on the next trading day is expected to be 12.79 with a mean absolute deviation of 0.21 and the sum of the absolute errors of 13.10.In general, regression methods applied to historical equity returns or prices series is an area of active research. In recent decades, new methods have been developed for robust regression of price series such as Applied Finance Core historical returns. These new methods are regression involving correlated responses such as growth curves and different regression methods accommodating various types of missing data. All forecast values on this page for Applied Finance Core are Simple Regression reference data derived from historical price series.
Simple Regression model is a single variable regression model that attempts to put a straight line through Applied Finance price points. This line is defined by its gradient or slope, and the point at which it intercepts the x-axis. Mathematically, assuming the independent variable is X and the dependent variable is Y, then this line can be represented as: Y = intercept + slope * X.

Simple Regression Price Forecast For the 22nd of March

Given 90 days horizon, the Simple Regression forecasted value of Applied Finance Core on the next trading day is expected to be 12.79 with a mean absolute deviation of 0.21 , mean absolute percentage error of 0.07 , and the sum of the absolute errors of 13.10 .
Please note that although there have been many attempts to predict Applied 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 Applied Finance's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Mutual Fund Forecast Pattern

Backtest Applied Finance  Applied Finance Price Prediction  Research Analysis  

Forecasted Value

For the next trading day, Macroaxis evaluates Applied Finance's predictive range by looking for statistically meaningful downside and upside boundaries. The projected forecast band currently runs from roughly 12.12 on the downside to about 13.45 on the upside.
Market Value
12.19
12.79
Expected Value
13.45
Upside

Model Predictive Factors

The below table displays some essential indicators generated by the model showing the Simple Regression forecasting method's relative quality and the estimations of the prediction error of Applied Finance mutual fund data series using in forecasting. Note that when a statistical model is used to represent Applied Finance 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 Criteria117.2477
BiasArithmetic mean of the errors None
MADMean absolute deviation0.2113
MAPEMean absolute percentage error0.0168
SAESum of the absolute errors13.1019
In general, regression methods applied to historical equity returns or prices series is an area of active research. In recent decades, new methods have been developed for robust regression of price series such as Applied Finance Core historical returns. These new methods are regression involving correlated responses such as growth curves and different regression methods accommodating various types of missing data.

Other Forecasting Options for Applied Finance

For both new and experienced investors in Applied, the ability to analyze Applied Finance's price movement is a fundamental investment skill. Price chart noise in Applied Mutual Fund can create false signals and mislead investment decisions.

Applied Finance Related Equities

The following equities are related to Applied Finance within the Large Value space and can be used for peer comparison, relative valuation, or portfolio diversification. Comparing Applied Finance 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

Applied Finance Market Strength Events

Tracking market strength indicators for Applied Finance provides context for understanding the momentum dynamics of the mutual fund in real time. These signals support informed decisions about when to enter or exit positions in Applied Finance Core for maximum return potential.

Applied Finance Risk Indicators

Properly assessing Applied Finance's risk indicators is a prerequisite for building reliable price forecasts. Identifying and quantifying the risks associated with Applied Finance's allows investors to make better-informed decisions about accepting or hedging their 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 Applied Finance

The amount of media and story coverage tied to Applied Finance Core 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 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.