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

Aspen Technology stock has a positive outlook with strong growth potential and low risk. It is predicted the stock will continue to rise in value, making it a good investment for those seeking long-term returns. However, investors should be aware of potential risks associated with the company's dependence on the energy industry and competition from larger software companies.

Aspen Technology reported 209.29M in Stock for its fiscal quarter ending in December of 2024. Data for Aspen Technology | AZPN - Stock 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.

Aspen Technology (AZPN) Stock: Can It Climb Higher?

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

Aspen Technology reported 63.25M in Outstanding Shares in January of 2025. Data for Aspen Technology | AZPN - Outstanding Shares 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.

Machine Learning stock prediction: AZPN Stock Prediction

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

AI-powered price forecasts for AZPN stock across different timeframes including weekly, monthly, yearly, and multi-year predictions.

Aspen Technology reported $16.72B in Market Capitalization this March of 2025, considering the latest stock price and the number of outstanding shares.Data for Aspen Technology | AZPN - Market Capitalization including historical, tables and charts were last updated by Trading Economics this last July in 2025.

This dataset is about stocks per day. It has 125 rows and is filtered where the stock is AZPN and the date is after the 10th of September 2024. It features 3 columns: stock, and opening price.

This dataset contains historical stock price data for Amazon from their initial public offering on the stock exchange until the current time. Data includes daily opening prices, closing prices, high and low prices, trading volumes and adjusted closing prices.

Aspen Technology reported $0 in Loan Capital for its fiscal quarter ending in December of 2024. Data for Aspen Technology | AZPN - Loan Capital including historical, tables and charts were last updated by Trading Economics this last July in 2025.

The price of Amazon shares traded on the Nasdaq stock exchange fluctuated significantly but increased for the most part during the period between 2010 and 2025, peaking at 237.68 U.S. dollar per share in January 2025. Expansion during the pandemic Due to the rise of online shopping worldwide during the Covid-19 pandemic, Amazon's share prices saw an increase as the company experienced dramatic growth. As a result, the company's net sales revenue increased by almost 400 billion U.S. dollars between 2019 to 2024, growing ever since. However, the surge in Amazon's operations significantly increased the company's fulfillment expenses and shipping costs after 2020. The shift towards offline shopping and cost increases after the pandemic resulted in significant layoffs in 2022. Amazon Web Services Amazon is not only the world's most valuable retailer but also the leader in the cloud computing industry through Amazon Web Services (AWS). AWS is a platform that offers storage, servers, and networking to individuals, businesses, and organizations. Amazon's success is driven by its excellence in diverse sectors, but AWS stands as the primary source of profit. The cloud service has consistently grown in profitability, generating nearly 40 billion U.S. dollars in profit in 2024.

Aspen Technology reported $13.94B in Assets for its fiscal quarter ending in December of 2024. Data for Aspen Technology | AZPN - Assets including historical, tables and charts were last updated by Trading Economics this last July in 2025.

Aspen Technology reported 1.3K in PE Price to Earnings for its fiscal quarter ending in December of 2022. Data for Aspen Technology | AZPN - PE Price to Earnings including historical, tables and charts were last updated by Trading Economics this last July in 2025.

Dataset Description

Overview:

This dataset contains the historical stock prices and related financial information for five major technology companies: Apple (AAPL), Microsoft (MSFT), Amazon (AMZN), Google (GOOGL), and Tesla (TSLA). The dataset spans a five-year period from January 1, 2019, to January 1, 2024. It includes key stock metrics such as Open, High, Low, Close, Adjusted Close, and Volume for each trading day.

Data Collection:

The data was sourced using the yfinance library in Python, which provides convenient access to historical market data from Yahoo Finance.

Contents:

The dataset contains the following columns:

Date: The trading date. Open: The opening price of the stock on that date. High: The highest price of the stock on that date. Low: The lowest price of the stock on that date. Close: The closing price of the stock on that date. Adj Close: The adjusted closing price, accounting for dividends and splits. Volume: The number of shares traded on that date. Ticker: The stock ticker symbol representing each company.

Amazon PE ratio as of June 17, 2025 is 30.55. Current and historical p/e ratio for Amazon (AMZN) from 2010 to 2025. The price to earnings ratio is calculated by taking the latest closing price and dividing it by the most recent earnings per share (EPS) number. The PE ratio is a simple way to assess whether a stock is over or under valued and is the most widely used valuation measure. Please refer to the Stock Price Adjustment Guide for more information on our historical prices.

Browse Amazon.com Inc (AMZN) market data. Get instant pricing estimates and make batch downloads of binary, CSV, and JSON flat files.

Nasdaq TotalView-ITCH is the proprietary data feed that provides full order book depth for Nasdaq market participants.

Origin: Directly captured at Equinix NY4 (Secaucus, NJ) with an FPGA-based network card and hardware timestamping. Synchronized to UTC with PTP.

Supported data encodings: DBN, CSV, JSON Learn more

Supported market data schemas: MBO, MBP-1, MBP-10, BBO-1s, BBO-1m, TBBO, Trades, OHLCV-1s, OHLCV-1m, OHLCV-1h, OHLCV-1d, Definition, Statistics, Status, Imbalance Learn more

Resolution: Immediate publication, nanosecond-resolution timestamps

Aspen Technology reported $20.34M in Net Income for its fiscal quarter ending in December of 2024. Data for Aspen Technology | AZPN - Net Income including historical, tables and charts were last updated by Trading Economics this last July in 2025.

📈 Daily Historical Stock Price Data for Amazon.com, Inc. (1997–2025)

A clean, ready-to-use dataset containing daily stock prices for Amazon.com, Inc. from 1997-05-15 to 2025-05-28. This dataset is ideal for use in financial analysis, algorithmic trading, machine learning, and academic research.

  🗂️ Dataset Overview

Company: Amazon.com, Inc. Ticker Symbol: AMZN Date Range: 1997-05-15 to 2025-05-28 Frequency: Daily Total Records: 7053 rows (one per trading day)… See the full description on the dataset page: https://huggingface.co/datasets/khaledxbenali/daily-historical-stock-price-data-for-amazoncom-inc-19972025.

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.

Amazon Stock: A Hold for the Next Month, But With Potential for Upside

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