Extreme Networks Stock Forward View - 20 Period Moving Average

EXTR Stock  USD 24.31  0.27  1.12%   
The 20 Period Moving Average output for Extreme Networks is derived from daily price data across the evaluation window. The error pattern reveals whether the model tracked prices consistently or diverged during volatile sessions. Parameters are re-estimated as new trading sessions are recorded, keeping the forecast current. The 20 Period Moving Average model projects Extreme Networks at 20.44 for the next trading day, below the most recent closing price. Extreme Networks's 20 Period Moving Average forecast is intended for short-term analytical reference.
The 20-period moving average forecast for Extreme Networks replaces each daily value with the mean of that value and the 20 preceding closing prices. This is a widely used smoothing window that spans approximately one month of trading data.

20 Period Moving Average Price Forecast For the 12th of May 2026

Over a 90-day horizon, the 20 Period Moving Average model forecasts Extreme Networks at 20.44 for the next trading day, with a mean absolute deviation of 1.96 , mean absolute percentage error of 0.1 , and sum of absolute errors of 80.38 .
This indicates moderate forecast accuracy — the model captures the general trend but not all short-term variation in Extreme Networks' price. This output is intended for short-term analytical reference.

Stock Forecast Pattern

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Forecasted Value

The projected range for Extreme Networks reflects the model's ability to define credible downside and upside scenarios for the next trading day. The current forecast range spans downside near 16.31 and upside near 24.57. The wide range indicates elevated uncertainty in short-term projections.
Market Value
24.31
20.44
Expected Value
24.57

Model Predictive Factors

The table below summarizes the 20 Period Moving Average model's error metrics for Extreme Networks stock. Lower MAD and MAPE values indicate tighter forecast accuracy. AIC measures relative model quality — lower values indicate less information loss and a better-fitting model. A large Bias suggests systematic over- or under-prediction.
AICAkaike Information Criteria83.241
BiasArithmetic mean of the errors -1.9605
MADMean absolute deviation1.9605
MAPEMean absolute percentage error0.0979
SAESum of the absolute errors80.381
The broader window aggressively filters short-term noise in Extreme Networks price data, producing a smooth trend line. This makes it useful for identifying the prevailing direction of Extreme Networks prices but slow to respond to reversals. The model is reliable only for very short-term projections (one to two periods).

Other Forecasting Options for Extreme Networks

Volatility clustering is a well-documented feature of Extreme Networks Stock price data where periods of large moves tend to follow other large moves. When Extreme Networks' RSI reaches extreme levels, it often precedes a short-term price correction or consolidation. Seasonal patterns in Extreme Networks' returns tend to persist when driven by structural factors like earnings calendars or index rebalancing.

Extreme Networks Related Equities

These stocks are related to Extreme Networks within the Information Technology space and can be used for peer review, pricing, or spreading risk. Key comparison metrics include price-to-earnings, profit margin, and revenue growth across Extreme Networks' peer group.
 Risk & Return  Correlation

Extreme Networks Market Strength Events

Accumulation/Distribution and Balance of Power for Extreme Networks reveal whether buying or selling pressure dominates recent sessions. Balance of Power trending positive indicates that buyers are consistently closing Extreme Networks near session highs. These signals help explain whether price direction and session structure are moving together for Extreme Networks.

Extreme Networks Risk Indicators

Risk indicator analysis for Extreme Networks quantifies how much price variability the stock has exhibited over the measurement window. Downside variance exceeding total variance indicates that negative moves in Extreme Networks have been larger or more frequent than positive ones. Mean deviation provides a more intuitive measure of typical price fluctuation than variance because it stays in the same units as Extreme Networks' price.
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.

Extreme Networks Short Properties

Short-interest data for Extreme Networks reveals whether bearish conviction in the market is gaining traction. This is applicable when the question is whether bearish pressure is starting to shape the market's reaction function.
Common Stock Shares Outstanding132.33 million
Cash And Short Term Investments231.75 million

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