FIRST EAGLE Mutual Fund Forward View - Simple Regression

FEAIX Fund  USD 30.89  0.05  0.16%   
The Simple Regression forecast shown here for FIRST EAGLE 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 Regression output serves as one input among many for analytical review.
The Simple Regression forecasted value of First Eagle Fund on the next trading day is expected to be 32.20 with a mean absolute deviation of 0.64 and the sum of the absolute errors of 39.64.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 First Eagle Fund historical returns. These new methods are regression involving correlated responses such as growth curves and different regression methods accommodating various types of missing data. This Simple Regression reference page for FIRST EAGLE presents model-generated projections from historical price data for informational purposes.
Simple Regression model is a single variable regression model that attempts to put a straight line through FIRST EAGLE 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 27th of March

Given 90 days horizon, the Simple Regression forecasted value of First Eagle Fund on the next trading day is expected to be 32.20 with a mean absolute deviation of 0.64 , mean absolute percentage error of 0.58 , and the sum of the absolute errors of 39.64 .
Please note that although there have been many attempts to predict FIRST 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 FIRST EAGLE'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

This next-day forecast for First Eagle Fund uses model performance to estimate practical downside and upside boundaries rather than a single point target alone. No forecasting approach has been shown to beat all others over time. Investors should treat any model output as a guide, not a guarantee.
Market Value
30.89
32.20
Expected Value
33.02
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 FIRST EAGLE mutual fund data series using in forecasting. Note that when a statistical model is used to represent FIRST EAGLE 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 Criteria119.3965
BiasArithmetic mean of the errors None
MADMean absolute deviation0.6393
MAPEMean absolute percentage error0.02
SAESum of the absolute errors39.6389
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 First Eagle Fund 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 FIRST EAGLE

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

FIRST EAGLE Related Equities

These stocks are related to FIRST EAGLE within the Large Value space and can be used for peer review, pricing, or spreading risk. Looking at FIRST EAGLE's pricing multiples next to these peers shows if the stock trades at a premium or discount.
 Risk & Return  Correlation

FIRST EAGLE Market Strength Events

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

FIRST EAGLE Risk Indicators

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

Coverage intensity for First Eagle Fund matters because narrative visibility can influence sentiment, participation, and volatility around the name. A disciplined read of coverage separates durable relevance from temporary noise.

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.