APPLIED MATERIALS Stock Forward View - Simple Regression

AP2 Stock   311.05  2.00  0.65%   
This page documents Simple Regression forecast output for APPLIED MATERIALS as reference data. The model is applied to historical closing prices and the resulting projection and error statistics are shown below. Key metrics including projected price and mean absolute deviation are summarized below. The reference data on this page covers both forecast levels and error statistics.
The Simple Regression forecasted value of APPLIED MATERIALS on the next trading day is expected to be 321.92 with a mean absolute deviation of 12.33 and the sum of the absolute errors of 752.16.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 MATERIALS historical returns. These new methods are regression involving correlated responses such as growth curves and different regression methods accommodating various types of missing data. APPLIED MATERIALS's Simple Regression reference values are drawn from available trading data and are presented for informational reference only.
Simple Regression model is a single variable regression model that attempts to put a straight line through APPLIED MATERIALS 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 26th of March

Given 90 days horizon, the Simple Regression forecasted value of APPLIED MATERIALS on the next trading day is expected to be 321.92 with a mean absolute deviation of 12.33 , mean absolute percentage error of 221.19 , and the sum of the absolute errors of 752.16 .
Please note that although there have been many attempts to predict APPLIED Stock 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 MATERIALS's next future price depends linearly on its previous prices and some stochastic term (i.e., imperfectly predictable multiplier).

Stock Forecast Pattern

Backtest APPLIED MATERIALS  APPLIED MATERIALS Price Prediction  Research Analysis  

Forecasted Value

The next-day forecast for APPLIED MATERIALS focuses on identifying predictive downside and upside bands that can frame a realistic trading range. The projected forecast band currently runs from roughly 318.73 on the downside to about 325.11 on the upside.
Market Value
311.05
318.73
Downside
321.92
Expected Value
325.11
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 MATERIALS stock data series using in forecasting. Note that when a statistical model is used to represent APPLIED MATERIALS stock, 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 Criteria123.5095
BiasArithmetic mean of the errors None
MADMean absolute deviation12.3305
MAPEMean absolute percentage error0.0439
SAESum of the absolute errors752.1613
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 MATERIALS 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 MATERIALS

MACD analysis of APPLIED tracks the relationship between two exponential moving averages of APPLIED MATERIALS's price. Many APPLIED MATERIALS's traders use Fibonacci levels to set entry and exit targets based on prior price swings. Average True Range measures the typical daily price swing for APPLIED, accounting for gaps. The frequency and magnitude of gaps reveal how much new information is being priced into APPLIED outside regular hours.

APPLIED MATERIALS Related Equities

Sizing up APPLIED MATERIALS against these stocks within the Materials space shows how it compares on key financial measures. Peer review on balance sheet metrics shows how APPLIED MATERIALS's capital structure stacks up against similar firms. Falling behind peers on key ratios may signal headwinds or execution issues worth looking into. These checks provide a starting point for deeper study of APPLIED MATERIALS's strengths and weak spots.
 Risk & Return  Correlation

APPLIED MATERIALS Market Strength Events

Market strength indicators for APPLIED MATERIALS assess how the stock responds to changes in investor sentiment. These signals support informed decisions about when to enter or exit APPLIED MATERIALS positions. Market strength signals help investors time APPLIED MATERIALS positions with greater precision and confidence. These tools add market timing discipline when analyzing APPLIED MATERIALS stock.

APPLIED MATERIALS Risk Indicators

Risk indicator analysis for APPLIED MATERIALS is a critical component of accurate price forecasting. Identifying and quantifying the risks associated with APPLIED MATERIALS's allows investors to make better-informed decisions. Understanding APPLIED MATERIALS's risk indicators is a fundamental step in managing investment exposure responsibly. Understanding the risk embedded in APPLIED MATERIALS's allows investors to decide whether to accept, reduce, or hedge 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 MATERIALS

Coverage intensity for APPLIED MATERIALS matters because narrative visibility can influence sentiment, participation, and volatility around the name. The stronger process compares story flow with performance, theme classification, and the level of short-term market interest.

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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.

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