Prices for Australia Stock Market Index (AU50) including live quotes, historical charts and news. Australia Stock Market Index (AU50) was last updated by Trading Economics this July 17 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: 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

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.

Advanced Semiconductor Engineering stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

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.

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.

📈 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.

Australia's main stock market index, the ASX200, rose to 8686 points on July 18, 2025, gaining 0.54% from the previous session. Over the past month, the index has climbed 1.90% and is up 8.96% 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.

In June 2025, nearly *********** options were traded on the Australian Securities Exchange (ASX). This was slightly above the monthly average of around *********** recorded since January 2020. However, The ASX options market is much lower than the volume of futures traded on the ASX. Options and futures are similar in that they are both financial derivatives that provide an investor the ability to buy (or sell) a financial asset for an agreed price at a certain point in time, but they differ in that futures require that the transaction take place, whereas options do not. Options and the coronavirus pandemic Coinciding with the global coronavirus (COVID-19) pandemic, the volume of options traded on the Australian Securities Exchange (ASX) spiked in **********. It is notable that the spike in terms of the value of options traded was much greater than in terms of volume. It is also notable that the majority of the spike in this month came from call options - which enable the option holder to purchase a financial instrument (like shares) for an agreed price at a date in the future. By contrast, put options enable holders to sell a financial instrument at an agreed value in the future. This suggests that the increased value for this month was driven by investors trying to capitalize on the pandemic by locking in lower prices for the future, with the (correct) assumption that prices would rise again in the following months. How is the value of derivatives calculated? Calculating the value of derivatives is different to an item like shares, in that derivatives contracts do not include the underlying asset price. Both options and futures are contracts which provide the ability to purchase a financial asset in the future for an agreed price – meaning the purchase of the contract does not include the purchasing of the asset itself. Generally, the ‘notional value’ is used to calculate the value of derivatives – which includes both the cost of the contract itself as well as the underlying asset. Note how options do not require the transaction take place, but yet the value of transaction is included. This one reason behind why, for example, banks in the U.S. and banks in the UK can hold derivates that are well above the national gross domestic product of their respective countries.

ASE Technology Holding may face revenue growth challenges due to increased competition in the semiconductor industry. However, its strong market position and focus on advanced packaging solutions could mitigate risks.

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

Australian Securities Exchange reported AUD13.83B 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.

Dataset Information

This dataset includes daily price data for various stock indices.

  Instruments Included

ADSMI: United Arab Emirates Stock Market (ADX General) - United Arab Emirates AEX: Netherlands Stock Market (AEX) - Netherlands (NL) AS30: Australian All - Australia (AU) AS51: Australia S&P/ASX 200 Stock Market Index - Australia (AU) AS52: ASX 50 - Australia (AU) ASE: Greece Stock Market (ASE) - Greece (GR) ATX: Austria Stock Market (ATX) - Austria (AT) BEL20:… See the full description on the dataset page: https://huggingface.co/datasets/paperswithbacktest/Indices-Daily-Price.

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

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 18 of 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.

ASE Tech's Strong Growth: How High Can It Go? (ASX)

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 S&P/ASX Small Ordinaries index saw a price return of 2,892.51 Australian dollars in July 2023. Due to the financial effects of the global coronavirus (COVID-19) pandemic, the price return for the index decreased significantly between the end of February and the end of March 2020.

ASX index performance affected by the coronavirus pandemic

The S&P/ASX Small Ordinaries index is a key benchmark for small-cap Australian companies. The index measures companies included in the S&P/ASX 300 but not in the S&P/ASX 100. In comparison, the S&P/ASX 200 index measures the performance of the 200 largest companies listed on the ASX. Due to the financial effects of the global coronavirus pandemic, it lost more than one-fifth of its value between the end of February and the end of March 2020. Since then, it has improved and surpassed its pre-corona level with its value peaking around 7.5 thousand index points in August 2021.

Financial markets in Australia

Financial markets in Australia are an integral part of the country's economy. The Australian Securities Exchange (ASX) is the country's primary stock exchange and, as of December 2022, it had a domestic market capitalization of approximately 2.46 trillion Australian dollars. As of April 2023, the largest company listed on the ASX was BHP Group Limited, with a total market capitalization of over 228 billion Australian dollars. The financial sector dominated the list of the largest Australian domestic companies, with five of the top 10 companies being either retail or investment banking groups. Overall, financial markets in Australia are diverse, and robust, attracting both local and international investors.

📈 Daily Historical Stock Price Data for ASE Technology Holding Co., Ltd. (2000–2025)

A clean, ready-to-use dataset containing daily stock prices for ASE Technology Holding Co., Ltd. from 2000-10-02 to 2025-05-28. This dataset is ideal for use in financial analysis, algorithmic trading, machine learning, and academic research.

  🗂️ Dataset Overview

Company: ASE Technology Holding Co., Ltd. Ticker Symbol: ASX Date Range: 2000-10-02 to 2025-05-28 Frequency: Daily Total… See the full description on the dataset page: https://huggingface.co/datasets/khaledxbenali/daily-historical-stock-price-data-for-ase-technology-holding-co-ltd-20002025.

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