Australia's main stock market index, the ASX200, fell to 8958 points on October 10, 2025, losing 0.13% from the previous session. Over the past month, the index has climbed 1.74% and is up 9.05% 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 October of 2025.

Australia's main stock market index, the ASX200, rose to 8788 points on September 26, 2025, gaining 0.17% from the previous session. Over the past month, the index has declined 1.93%, though it remains 7.01% higher than a year ago, 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 September of 2025.

Graph and download economic data for Volatility of Stock Price Index for Australia (DDSM01AUA066NWDB) from 1984 to 2021 about stocks, volatility, Australia, price index, indexes, and price.

Australia: Stock price volatility, percent: The latest value from 2021 is 21.7 percent, a decline from 22.26 percent in 2020. In comparison, the world average is 20.14 percent, based on data from 87 countries. Historically, the average for Australia from 1984 to 2021 is 14.91 percent. The minimum value, 7.56 percent, was reached in 2005 while the maximum of 34.44 percent was recorded in 1988.

The report covers Australia C4ISR Companies and the market is Segmented by Platform (Land, Air, Naval, and Space) . The report offers market size and forecasts in value (USD Million) for the above segment.

Australia ASX Index: S&P/ASX 300 data was reported at 8,060.900 Point in Apr 2025. This records an increase from the previous number of 7,782.100 Point for Mar 2025. Australia ASX Index: S&P/ASX 300 data is updated monthly, averaging 4,617.150 Point from May 1992 (Median) to Apr 2025, with 396 observations. The data reached an all-time high of 8,460.400 Point in Jan 2025 and a record low of 1,419.300 Point in Oct 1992. Australia ASX Index: S&P/ASX 300 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 S&P/ASX 300 Index (XKO) provides additional depth and coverage to the S&P/ASX 200 whilst maintaining strict liquidity guidelines. It provides up to an additional 100 small-cap stocks to the S&P/ASX 200. The S&P/ASX 300 Index forms the basis for the Vanuard Australian Shares Index 300 Exchange Traded Fund (ETF).

Stock price volatility in Australia was reported at 21.7 in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Australia - Stock price volatility - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2025.

Stock market return (%, year-on-year) in Australia was reported at 19.3 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Australia - Stock market return (%, year-on-year) - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2025.

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)

Graph and download economic data for Capital Stock at Constant National Prices for Australia (RKNANPAUA666NRUG) from 1950 to 2019 about stocks, Australia, capital, and 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.

NAB NATIONAL AUSTRALIA BANK 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

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.

The price to earning (PE) ratios of REITs in Australia was lower than the PE ratio of the total market and the real estate sector as of June 2025. REITs are companies that own or finance rental real estate. One of their major benefit is liquidity: Though not all REITs are publicly traded, many of the major ones are, which allows investors to easily buy and sell shares. Because REITs pay out most of their taxable income to shareholders as dividends, they typically do not pay any corporate income tax. As of June 2025, the PE ratio of REITs in Australia stood at *****, with the earnings of the market forecast to grow ** percent annually. The PE ratio is a valuation metric which is calculated as the ratio of the total market cap to the total earnings. A higher PE ratio means that the market cap has grown higher than the earnings - a sign of high investor confidence, but also that the market may be overpriced.

Australian Securities Exchange stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

Australia Data Center Power Market Report Segments the Industry Into Component (Electrical Solutions, Service), Data Center Type (Hyperscaler/Cloud Service Providers and More), Data Center Size(Small-Sized Data Centers, Medium-Sized Data Centers, and More), and Tier Level (Tier I and II and More). The Market Forecasts are Provided in Terms of Value (USD).

The revenue change in the e-commerce market in Australia was forecast to continuously decrease between 2025 and 2029 by in total *** percentage points. According to this forecast, in 2029, the revenue change will have decreased for the fourth consecutive year to **** percent. Find further information concerning the revenue in the e-commerce market in Czechia and the penetration rate in the e-commerce market in the United Kingdom.The Statista Market Insights cover a broad range of additional markets.

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.

AR3 AUSTRALIAN RARE EARTHS 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

Australia Cybersecurity Market Report Segments the Industry Into by Offering (Solutions, Services), by Deployment Mode (Cloud, On-Premise), by Organization Size (SMEs, Large Enterprises), and by End User (BFSI, Healthcare, IT and Telecom, Industrial & Defense, Retail, Energy and Utilities, Manufacturing, Others). Get Five Years of Historical Data Alongside Five-Year Market Forecasts.

The price per unit is forecast to experience significant growth in all segments in 2030. The trend observed from 2020 to 2030 remains consistent throughout the entire forecast period. There is a continuous increase in the price per unit across all segments. Notably, the Cigars segment achieves the highest value of **** U.S. dollars at 2030. Find further statistics on other topics such as a comparison of the revenue in Russia and a comparison of the price per unit in Suriname. The Statista Market Insights cover a broad range of additional markets.

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.

A2B A2B AUSTRALIA 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