Canada's main stock market index, the TSX, fell to 27868 points on August 15, 2025, losing 0.17% from the previous session. Over the past month, the index has climbed 2.63% and is up 20.88% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Canada. Canada Stock Market Index (TSX) - values, historical data, forecasts and news - updated on August of 2025.

Prices for Canada TSX 60 Stock Market Index including live quotes, historical charts and news. Canada TSX 60 Stock Market Index was last updated by Trading Economics this August 15 of 2025.

Prices for Canada Stock Market Index (TSX) including live quotes, historical charts and news. Canada Stock Market Index (TSX) was last updated by Trading Economics this August 15 of 2025.

Canada TSX/Venture Exchange: Trade: Advances data was reported at 6,621.000 Unit in Feb 2019. This records a decrease from the previous number of 7,893.000 Unit for Jan 2019. Canada TSX/Venture Exchange: Trade: Advances data is updated monthly, averaging 6,727.500 Unit from May 2002 (Median) to Feb 2019, with 202 observations. The data reached an all-time high of 11,235.000 Unit in Mar 2011 and a record low of 3,095.000 Unit in Aug 2002. Canada TSX/Venture Exchange: Trade: Advances data remains active status in CEIC and is reported by Toronto Stock Exchange. The data is categorized under Global Database’s Canada – Table CA.Z003: Toronto Stock Exchange: Trade.

Canada TSX: Trade: Advances data was reported at 17,420.000 Unit in Feb 2019. This records a decrease from the previous number of 20,564.000 Unit for Jan 2019. Canada TSX: Trade: Advances data is updated monthly, averaging 16,246.000 Unit from May 2002 (Median) to Feb 2019, with 202 observations. The data reached an all-time high of 20,564.000 Unit in Jan 2019 and a record low of 9,473.000 Unit in Sep 2002. Canada TSX: Trade: Advances data remains active status in CEIC and is reported by Toronto Stock Exchange. The data is categorized under Global Database’s Canada – Table CA.Z003: Toronto Stock Exchange: Trade.

This table contains 25 series, with data for years 1956 - present (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Toronto Stock Exchange Statistics (25 items: Standard and Poor's/Toronto Stock Exchange Composite Index; high; Standard and Poor's/Toronto Stock Exchange Composite Index; close; Toronto Stock Exchange; oil and gas; closing quotations; Standard and Poor's/Toronto Stock Exchange Composite Index; low ...).

Canada TSX/Venture Exchange: Traded: Total data was reported at 20,627.000 Unit in Feb 2019. This records a decrease from the previous number of 23,111.000 Unit for Jan 2019. Canada TSX/Venture Exchange: Traded: Total data is updated monthly, averaging 24,506.500 Unit from May 2002 (Median) to Feb 2019, with 202 observations. The data reached an all-time high of 36,057.000 Unit in Mar 2011 and a record low of 17,074.000 Unit in Aug 2002. Canada TSX/Venture Exchange: Traded: Total data remains active status in CEIC and is reported by Toronto Stock Exchange. The data is categorized under Global Database’s Canada – Table CA.Z003: Toronto Stock Exchange: Trade.

Canada TSX: Traded: Total data was reported at 35,581.000 Unit in Feb 2019. This records a decrease from the previous number of 40,587.000 Unit for Jan 2019. Canada TSX: Traded: Total data is updated monthly, averaging 37,954.000 Unit from May 2002 (Median) to Feb 2019, with 202 observations. The data reached an all-time high of 44,045.000 Unit in Mar 2011 and a record low of 24,780.000 Unit in Aug 2002. Canada TSX: Traded: Total data remains active status in CEIC and is reported by Toronto Stock Exchange. The data is categorized under Global Database’s Canada – Table CA.Z003: Toronto Stock Exchange: Trade.

Canadian Financial Markets Research Centre (CFMRC) summary information database (or CFMRC TSX database for short) includes daily and monthly Toronto Stock Exchange trading information about specific securities as well as information on "price adjustments" such as dividends, stock splits, recapitalizations, etc. The database also includes daily and monthly indexes containing information on daily and monthly index levels as well as selected other financial markets information. CFMRC/TSX highlights: expanded daily data set includes opening as well as closing data for: prices; bids; asks; trades; and volumes, amongst other information expanded monthly data set includes: betas; earnings per share; volume; and transactions, amongst other data expanded daily and monthly index data sets which include: a selection of interest and exchange rates; TMX Group indices; new under- and over- $2.00 indices, as well as other data CHASS is maintaining two web interfaces: CFMRC/TSX annual update - updated once a year, usually at the beginning of the calendar year. CFMRC/TSX quarterly update - updated four times a year.

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.

RY:TSX Royal Bank of Canada

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

Canada TSX/Venture Exchange: Trade: Declines data was reported at 6,950.000 Unit in Feb 2019. This records a decrease from the previous number of 7,598.000 Unit for Jan 2019. Canada TSX/Venture Exchange: Trade: Declines data is updated monthly, averaging 7,356.000 Unit from May 2002 (Median) to Feb 2019, with 202 observations. The data reached an all-time high of 12,769.000 Unit in Mar 2011 and a record low of 3,045.000 Unit in Aug 2002. Canada TSX/Venture Exchange: Trade: Declines data remains active status in CEIC and is reported by Toronto Stock Exchange. The data is categorized under Global Database’s Canada – Table CA.Z003: Toronto Stock Exchange: Trade.

Net-Buyback-Yield Time Series for TMX Group Limited. TMX Group Limited operates exchanges, markets, and clearinghouses primarily for capital markets in Canada, the United States, the United Kingdom, Germany, and internationally. It operates in four segments: Global Solutions, Insights & Analytics; Capital Formation; Derivatives Trading & Clearing; and Equities and Fixed Income Trading & Clearing. The Global Solutions, Insights & Analytics segment delivers equities and index data, as well as integrated data sets for the proprietary and third party analytics to help clients in making trading and investment decisions; and provides solutions to European and global wholesale energy markets for price discovery, trade execution, post-trade transparency, and straight through processing. The Capital Formation segment operates Toronto Stock Exchange, a national stock exchange for the senior equities market; TSX Venture Exchange, a national stock exchange for the public venture equity market; TSX Trust that provides corporate trust, registrar, transfer agency, and foreign exchange services; and Newsfile, a news dissemination and regulatory filing provider. The Derivatives Trading & Clearing segment operates Montreal Exchange, a national derivatives exchange; Canadian Derivatives Clearing Corporation, a clearinghouse for options and futures contracts; BOX, a US equity operations market; and various over-the-counter products and fixed income repurchase agreements. The Equities and Fixed Income Trading & Clearing segment engages in the trading operations of Toronto Stock Exchange, TSX Venture Exchange, and TSX Alpha Exchange; CDS Clearing, an automated facility for the clearing and settlement of equities and fixed income transactions, and custody of securities; and provision of fixed income inter-dealer brokerage services. The company was formerly known as Maple Group Acquisition Corporation and changed its name to TMX Group Limited in August 2012. TMX Group Limited was incorporated in 2011 and is headquartered in Toronto, Canada.

Stock market return (%, year-on-year) in Canada was reported at 23.7 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Canada - Stock market return (%, year-on-year) - actual values, historical data, forecasts and projections were sourced from the World Bank on August of 2025.

Canada TSX: Trade: Declines data was reported at 13,650.000 Unit in Feb 2019. This records a decrease from the previous number of 15,403.000 Unit for Jan 2019. Canada TSX: Trade: Declines data is updated monthly, averaging 16,064.000 Unit from May 2002 (Median) to Feb 2019, with 202 observations. The data reached an all-time high of 21,671.000 Unit in Oct 2018 and a record low of 10,313.000 Unit in Aug 2002. Canada TSX: Trade: Declines data remains active status in CEIC and is reported by Toronto Stock Exchange. The data is categorized under Global Database’s Canada – Table CA.Z003: Toronto Stock Exchange: Trade.

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.

CP:TSX Canadian Pacific Railway 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

Canada TSX Venture Exchange: Issues Traded: Unchanged data was reported at 9,012.000 Unit in Apr 2025. This records a decrease from the previous number of 9,274.000 Unit for Mar 2025. Canada TSX Venture Exchange: Issues Traded: Unchanged data is updated monthly, averaging 10,428.000 Unit from May 2002 (Median) to Apr 2025, with 276 observations. The data reached an all-time high of 14,471.000 Unit in Apr 2013 and a record low of 7,056.000 Unit in Feb 2019. Canada TSX Venture Exchange: Issues Traded: Unchanged data remains active status in CEIC and is reported by TMX Group Limited. The data is categorized under Global Database’s Canada – Table CA.Z004: TMX Group Limited: Trade.

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.

CNQ:TSX Canadian Natural Resources 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

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.

XSB:TSX iShares Core Canadian Short Term Bond Index ETF

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

Foreign Stock Investment in Canada increased to -2790 CAD Million in May from -9460 CAD Million in April of 2025. This dataset provides the latest reported value for - Canada Foreign Stock Investment - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus 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.

CNR:TSX Canadian National Railway Company

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