Performant Financial stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

PFMT Performant Financial Corporation Common Stock

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Performant Financial reported $206.1M in Market Capitalization this April of 2024, considering the latest stock price and the number of outstanding shares.Data for Performant Financial | PFMT - Market Capitalization including historical, tables and charts were last updated by Trading Economics this last July in 2025.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Performant Financial (PFMT): Will Performance Pay Off?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Performant Financial reported 76.92M in Outstanding Shares in April of 2024. Data for Performant Financial | PFMT - Outstanding Shares including historical, tables and charts were last updated by Trading Economics this last June in 2025.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

PFMT Stock Forecast: A Sell For The Next 6 Month

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Performant Financial reported $101.84M in Assets for its fiscal quarter ending in September of 2024. Data for Performant Financial | PFMT - Assets including historical, tables and charts were last updated by Trading Economics this last July in 2025.

Performant Financial reported $-2384000 in Net Income for its fiscal quarter ending in September of 2024. Data for Performant Financial | PFMT - Net Income including historical, tables and charts were last updated by Trading Economics this last July in 2025.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Performant Financial Flurry: A Dividend Mirage? (PFMT)

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Performant Financial reported $38.33M in Current Assets for its fiscal quarter ending in September of 2024. Data for Performant Financial | PFMT - Current Assets including historical, tables and charts were last updated by Trading Economics this last July in 2025.

Performant Financial reported $33.67M in Operating Expenses for its fiscal quarter ending in September of 2024. Data for Performant Financial | PFMT - Operating Expenses including historical, tables and charts were last updated by Trading Economics this last July in 2025.

Performant Financial reported $8M in Debt for its fiscal quarter ending in September of 2024. Data for Performant Financial | PFMT - Debt including historical, tables and charts were last updated by Trading Economics this last July in 2025.

Performant Financial reported $93K in Interest Income for its fiscal quarter ending in September of 2024. Data for Performant Financial | PFMT - Interest Income including historical, tables and charts were last updated by Trading Economics this last July in 2025.

Performant Financial reported $14.37M in Current Liabilities for its fiscal quarter ending in September of 2024. Data for Performant Financial | PFMT - Current Liabilities including historical, tables and charts were last updated by Trading Economics this last July in 2025.

Performant Financial reported $-2149000 in EBIT for its fiscal quarter ending in September of 2024. Data for Performant Financial | PFMT - Ebit including historical, tables and charts were last updated by Trading Economics this last July in 2025.

Performant Financial reported $8M in Loan Capital for its fiscal quarter ending in June of 2024. Data for Performant Financial | PFMT - Loan Capital including historical, tables and charts were last updated by Trading Economics this last July in 2025.

Performant Financial reported $714K in EBITDA for its fiscal quarter ending in September of 2023. Data for Performant Financial | PFMT - Ebitda including historical, tables and charts were last updated by Trading Economics this last July in 2025.

Performant Financial reported $-2741000 in Operating Profit for its fiscal quarter ending in June of 2024. Data for Performant Financial | PFMT - Operating Profit including historical, tables and charts were last updated by Trading Economics this last July in 2025.

Performant Financial reported $719K in Trade Creditors for its fiscal quarter ending in September of 2024. Data for Performant Financial | PFMT - Trade Creditors including historical, tables and charts were last updated by Trading Economics this last July in 2025.

Performant Financial reported $27.61M in Trade Debtors for its fiscal quarter ending in September of 2024. Data for Performant Financial | PFMT - Trade Debtors including historical, tables and charts were last updated by Trading Economics this last July in 2025.