Australia's main stock market index, the ASX200, fell to 8580 points on July 11, 2025, losing 0.11% from the previous session. Over the past month, the index has climbed 0.18% and is up 7.80% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Australia. Australia Stock Market Index - values, historical data, forecasts and news - updated on July of 2025.

The S&P/ASX 200 index, the most prominent index of stocks listed on the Australian Securities Exchange (ASX), lost over one fifth of its value between the end of February and the end of March 2020, owing to the economic impact of the global coronavirus (COVID-19) pandemic. It has since recovered, and surpassed its pre-corona level in April 2021. Despite fluctuations, it reached its highest value in January 2025 at 8532.3 during this period.The S&P/ASX 200 index is considered the benchmark index for the Australian share market and contains the 200 largest companies listed on the ASX.

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.

ASX 200: Poised for a Record-Breaking Ascent?

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

📈 Daily Historical Stock Price Data for ASX Limited (1998–2025)

A clean, ready-to-use dataset containing daily stock prices for ASX Limited from 1998-10-30 to 2025-05-28. This dataset is ideal for use in financial analysis, algorithmic trading, machine learning, and academic research.

  🗂️ Dataset Overview

Company: ASX Limited Ticker Symbol: ASX.AX Date Range: 1998-10-30 to 2025-05-28 Frequency: Daily Total Records: 6768 rows (one per trading day)

  🔢 Columns… See the full description on the dataset page: https://huggingface.co/datasets/khaledxbenali/daily-historical-stock-price-data-for-asx-limited-19982025.

Advanced Semiconductor Engineering 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.

Will the ASX 200 Index Continue its Ascent?

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

Key information about Australia S&P/ASX 200

• Australia S&P/ASX 200 closed at 8,172.4 points in Feb 2025, compared with 8,532.3 points at the previous month end
• Australia Equity Market Index: Month End: ASX: S&P/ASX 200 data is updated monthly, available from May 1992 to Feb 2025, with an average number of 4,604.3 points
• The data reached an all-time high of 8,532.3 points in Jan 2025 and a record low of 1,428.8 points in Oct 1992

The S&P/ASX 200 Index (XJO) is recognised as the investable benchmark for the Australian equity market, it addresses the needs of investment managers to benchmark against a portfolio characterised by sufficient size and liquidity. The S&P/ASX 200 is comprised of the S&P/ASX 100 plus an additional 100 stocks. It forms the basis for the S&P/ASX 200 Index Future and Options and the SPDR S&P/ASX 200 Exchange Traded Fund (ETF)

Australian Securities Exchange reported 193.88M in Outstanding Shares in January of 2025. Data for Australian Securities Exchange | ASX - Outstanding Shares including historical, tables and charts were last updated by Trading Economics this last July in 2025.

Predictions hold that the S&P/ASX 200 index may fluctuate within a wide range. Bulls foresee a surge driven by positive economic data, strong corporate earnings, and central bank easing. However, bears anticipate downward pressure due to geopolitical uncertainties, inflation concerns, and potential earnings revisions. Risks include economic slowdown, interest rate hikes, and a resurgence of COVID-19 cases, which could push the index lower.

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.

ASX 200 to See Modest Gains Amid Global Uncertainty, Experts Say.

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

The average value of daily trades on Australian equity markets jumped sharply in the first quarter of 2020, increasing from around 6.5 billion Australian dollars in the previous quarter to over 9.4 billion Australian dollars. While this spike was likely due to the economic impact of the coronavirus (COVID-19) pandemic, values did not return back to their trend value for the previous two years. While the quarterly average between Q1 2017 and Q4 2019 was around 6.4 billion U.S. dollars, the average between the first quarter of 2020 and the first quarter of 2024 was over eight billion Australian dollars. In general, between 80 and 85 percent of these the total values traded was on the Australian Securities Exchange (ASX), with the remainder being on the Chi-X Australia platform, which is operated by the Chicago Board Options Exchange (CBOE).

Australian Securities Exchange reported AUD13.75B in Market Capitalization this July of 2025, considering the latest stock price and the number of outstanding shares.Data for Australian Securities Exchange | ASX - Market Capitalization including historical, tables and charts were last updated by Trading Economics this last July in 2025.

Australia ASX Index: All Ordinaries data was reported at 8,341.000 Jan1982=500 in Apr 2025. This records an increase from the previous number of 8,053.200 Jan1982=500 for Mar 2025. Australia ASX Index: All Ordinaries data is updated monthly, averaging 3,539.200 Jan1982=500 from Mar 1984 (Median) to Apr 2025, with 494 observations. The data reached an all-time high of 8,789.700 Jan1982=500 in Jan 2025 and a record low of 654.900 Jan1982=500 in May 1984. Australia ASX Index: All Ordinaries data remains active status in CEIC and is reported by Australian Securities Exchange. The data is categorized under Global Database’s Australia – Table AU.Z001: Australian Stock Exchange: Indices. The All Ordinaries Index (XAO) is Australia's premier market indicator. The index represents the 500 largest companies listed on the ASX. Market capitalisation is the only eligibility requirement of constituents, as liquidity is not considered, with the exception of foreign domiciled companies.

Australian Securities Exchange reported 26.58 in PE Price to Earnings for its fiscal semester ending in June of 2024. Data for Australian Securities Exchange | ASX - PE Price to Earnings including historical, tables and charts were last updated by Trading Economics this last July in 2025.

The Australian Securities Exchange (ASX) was established in July 2006 after the Australian Stock Exchange merged with the Sydney Futures Exchange, making it one of the top 20 global exchange groups by market capitalization. ASX facilitates trading in leading stocks, ETFs, derivatives, fixed income, commodities, and energy, commanding over 80% of the market share in the Australian Cash Market, with the S&P/ASX 200 as its main index. We offer comprehensive real-time market information services for all instruments in the ASX Level 1 and Level 2 (full market depth) products, and also provide Level 1 data as a delayed service. You can access this data through various means tailored to your specific needs and workflows, whether for trading via electronic low latency datafeeds, using our desktop services equipped with advanced analytical tools, or through our end-of-day valuation and risk management products.

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.

ASX ASX LIMITED

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

The most recent stock split for ASE Technology Holding (ASX) was a 1:1 split on August 13, 2008. The combined total of all historical stock splits for ASE Technology Holding result in 1.75692 current shares for every original share available at the IPO in 2000.

Between January 2010 and June 2025, the total market capitalization of domestic companies listed on the Australian Securities Exchange (ASX) grew from **** trillion Australian dollars to **** trillion Australian dollars. While the overall trend was upward, the growth curve was far from linear. The two most notable periods of decline were from March to September 2011, and the crash of March 2020 caused by the global coronavirus (COVID-19) pandemic.

Prices for Australia Stock Market Index (All Ordinaries Composite) including live quotes, historical charts and news. Australia Stock Market Index (All Ordinaries Composite) was last updated by Trading Economics this July 13 of 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.

ASX 200 Index: Will the Momentum Continue?

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