Solid Power Stock Forward View - Polynomial Regression

SLDP Stock  USD 3.08  0.16  5.48%   
Solid Power's Polynomial Regression forecast is generated from the selected price series and evaluated against observed values. Forecast accuracy depends on how stable the recent price trend has been — trending markets suit some models better than others. The forecast is recalculated with each session so it does not rely on stale inputs. A small Bias confirms the model is not systematically over- or under-predicting. The Polynomial Regression model projects Solid Power at 3.36 for the next trading day, above the most recent closing price. All values shown are model-generated projections and should be evaluated alongside other analytical inputs.
Polynomial regression for Solid Power 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 11th of May 2026

Over a 90-day horizon, the Polynomial Regression model forecasts Solid Power at 3.36 for the next trading day, with a mean absolute deviation of 0.15 , mean absolute percentage error of 0.05 , and sum of absolute errors of 9.42 .
This represents a tight forecast with good short-term tracking of Solid Power's price movement. This output is intended for short-term analytical reference.

Stock Forecast Pattern

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Forecasted Value

The projected range for Solid Power reflects the model's ability to define credible downside and upside scenarios for the next trading day. Downside is estimated near 0.03 and upside near 7.23. The wide range indicates elevated uncertainty in short-term projections.
Market Value
3.08
3.36
Expected Value
7.23

Model Predictive Factors

The table below summarizes the Polynomial Regression model's error metrics for Solid Power 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 Criteria114.9216
BiasArithmetic mean of the errors None
MADMean absolute deviation0.1545
MAPEMean absolute percentage error0.0469
SAESum of the absolute errors9.4245
The model takes the form: Y = a0 + a1*X + a2*X2 + a3*X3 + ... + am*Xm. Higher-degree polynomials fit Solid Power historical data more closely but are more prone to overfitting, which can produce unreliable extrapolations beyond the observed price range.

Other Forecasting Options for Solid Power

Bollinger Bands applied to Solid Power Stock price data measure how far Solid Power has deviated from its recent average relative to its own volatility. This distinction drives the choice of forecasting model applied to Solid Power's price data. On-balance volume for Solid Power Stock creates a running indicator of buying versus selling pressure in Solid Power. Price departures from the channel boundary often mean-revert, offering tactical signals for Solid Power's.

Solid Power Related Equities

These stocks are related to Solid Power within the Industrials space and can be used for peer review, pricing, or spreading risk. Growth rate gaps between Solid Power and its peers often explain pricing differences in the market. How Solid Power ranks within this group can shift over time as the competitive picture changes. This type of review is most informative when done often to track how positions shift over time.
 Risk & Return  Correlation

Solid Power Market Strength Events

Market strength indicators for Solid Power quantify how the stock responds to shifts in volume and sentiment. These indicators capture shifts in momentum that may precede significant price moves in Solid Power. The Market Facilitation Index measures how efficiently price moves relative to volume — rising MFI with rising volume signals strong trend participation. Monitoring these indicators for Solid Power through complete market cycles reveals recurring patterns.

Solid Power Risk Indicators

Analyzing Solid Power's risk indicators separates symmetric price swings from asymmetric downside exposure. Understanding and quantifying the risks present in Solid Power helps place recent price behavior in context. These metrics are most informative when compared against similar equities with comparable growth profiles and market capitalization. When semi-deviation is high relative to standard deviation, Solid Power's losses have been disproportionately large compared to gains.
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.

Solid Power Short Properties

Short-interest data for Solid Power reveals whether bearish conviction in the market is gaining traction. A disciplined short-interest review can make timing decisions more informed under rising skepticism.
Common Stock Shares Outstanding184.9 million
Cash And Short Term Investments251.21 million