Cambium Networks Stock Forward View - Polynomial Regression

CMBM Stock  USD 0.30  0.0001  0.03%   
The Polynomial Regression output for Cambium Networks Corp 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 Polynomial Regression model projects Cambium Networks at 0.52 for the next trading day, above the most recent closing price. Cambium Networks's Polynomial Regression forecast is intended for short-term analytical reference.
Polynomial regression for Cambium Networks fits a curved line through historical price points using time as the independent variable. Unlike simple regression, which fits only a straight line, polynomial regression can capture nonlinear price trends including acceleration and deceleration.

Polynomial Regression Price Forecast For the 9th of May

Over a 90-day horizon, the Polynomial Regression model forecasts Cambium Networks at 0.52 for the next trading day, with a mean absolute deviation of 0.21 , mean absolute percentage error of 0.69 , and sum of absolute errors of 12.71 .
This indicates weak forecast accuracy — the model has limited predictive reliability for Cambium Networks' at this horizon. This output is intended for short-term analytical reference.

Stock Forecast Pattern

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Forecasted Value

This forecast for Cambium Networks frames the expected trading range using downside and upside bounds rather than a single point target. The model places downside around 0.003 and upside around 73.62 for the next session. The wide range indicates elevated uncertainty in short-term projections.
Market Value
0.30
0.52
Expected Value
73.62

Model Predictive Factors

The table below summarizes the Polynomial Regression model's error metrics for Cambium 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 Criteria115.6963
BiasArithmetic mean of the errors None
MADMean absolute deviation0.2084
MAPEMean absolute percentage error0.6869
SAESum of the absolute errors12.7105
The model takes the form: Y = a0 + a1*X + a2*X2 + a3*X3 + ... + am*Xm. Higher-degree polynomials fit Cambium Networks Corp historical data more closely but are more prone to overfitting, which can produce unreliable extrapolations beyond the observed price range.

Other Forecasting Options for Cambium Networks

Relative Strength Index values for Cambium Networks measure the speed and magnitude of recent price changes. Recognizing these clusters in Cambium Networks' returns informs position size and stop-loss calibration. Candlestick pattern analysis of Cambium Networks Stock daily data reveals short-term reversal or continuation signals.

Cambium Networks Related Equities

The stocks listed below are peers of Cambium Networks within the Information Technology space and offer context for ranking and strength. Growth rate gaps between Cambium Networks and its peers often explain pricing differences in the market.
 Risk & Return  Correlation

Cambium Networks Market Strength Events

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

Cambium Networks Risk Indicators

Risk indicator analysis for Cambium Networks quantifies how much price variability the stock has exhibited over the measurement window. Downside variance exceeding total variance indicates that negative moves in Cambium 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 Cambium 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.

Cambium Networks Short Properties

Short-interest data for Cambium 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 Outstanding27.52 million
Cash And Short Term Investments11.06 million