Canada's main stock market index, the TSX, fell to 26419 points on June 9, 2025, losing 0.04% from the previous session. Over the past month, the index has climbed 3.47% and is up 19.70% 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 June of 2025.

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 ...).

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 June 9 of 2025.

The S&P/TSX Composite index, comprised of around 250 of the largest companies listed on the Toronto Stock Exchange, lost around one third of its value between February 16 and March 15, 2020, owing to the economic impact of the global coronavirus (COVID-19) pandemic. It has since recovered, surpassing its pre-corona level in early 2021.

The S&P/TSX Composite index is considered benchmark index for Canada, and represents around 70 percent of the total market capitalization of the Toronto Stock Exchange, which is the main Canadian stock exchange.

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 June 9 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.

Where Will CAE:TSX Stock Be in 6 Month?

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

Explore LSEG's Toronto Stock Exchange (TSX) Market Data, representing a broad range of businesses from Canada and abroad.

The S&P/TSX Composite index (CAD) closed at 24,727.94 points at the end of 2024. This was an increase over the past year. What is the S&P/TSX Composite index? The S&P/TSX Composite index is a Canadian index that measures stocks on the Toronto Stock Exchange, one of the largest stock exchanges worldwide. A stock market index tracks the development of a group of stock prices. It allows to get a quick idea of economic climate in a given region. Canadian stock market The size of a stock exchange is basically the sum of market capitalizations of companies being traded on this stock exchange. The largest companies in terms of market capitalization in Canada in 2024 were the Royal Bank of Canada, and Toronto Dominion Bank. The total market capitalization of listed domestic companies in Canada equaled to 2.74 trillion U.S. dollars in 2022.

This table contains 14 series, with data starting from 1953 (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 ...), Stock market statistics (14 items: Toronto Stock Exchange; value of shares traded; United States common stocks; Dow-Jones industrials; high; United States common stocks; Dow-Jones industrials; low; Toronto Stock Exchange; volume of shares traded ...).

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.

CM:TSX Stock Forecast: A Buy For The Next 6 Month

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

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 June of 2025.

Key information about Canada S&P/TSX Composite

• Canada S&P/TSX Composite closed at 25,393.5 points in Feb 2025, compared with 25,533.1 points at the previous month end
• Canada Equity Market Index: Month End: TMX: S&P/TSX Composite data is updated monthly, available from May 2002 to Feb 2025, with an average number of 13,818.0 points
• The data reached an all-time high of 25,648.0 points in Nov 2024 and a record low of 6,180.4 points in Sep 2002

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.

Techsalerator offers an extensive dataset of End-of-Day Pricing Data for all 800 companies listed on the Canadian Securities Exchange (XCNQ) in Canada. This dataset includes the closing prices of equities (stocks), bonds, and indices at the end of each trading session. End-of-day prices are vital pieces of market data that are widely used by investors, traders, and financial institutions to monitor the performance and value of these assets over time.

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Top 5 used data fields in the End-of-Day Pricing Dataset for Canada:

1. Equity Closing Price :The closing price of individual company stocks at the end of the trading day.This field provides insights into the final price at which market participants were willing to buy or sell shares of a specific company.

2. Bond Closing Price: The closing price of various fixed-income securities, including government bonds, corporate bonds, and municipal bonds. Bond investors use this field to assess the current market value of their bond holdings.

3. Index Closing Price: The closing value of market indices, such as the Botswana stock market index, at the end of the trading day. These indices track the overall market performance and direction.

4. Equity Ticker Symbol: The unique symbol used to identify individual company stocks. Ticker symbols facilitate efficient trading and data retrieval.

5. Date of Closing Price: The specific trading day for which the closing price is provided. This date is essential for historical analysis and trend monitoring.

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Top 5 financial instruments with End-of-Day Pricing Data in Canada:

S&P/TSX Composite Index: The primary stock market index in Canada, tracking the performance of domestic companies listed on the Toronto Stock Exchange (TSX). It provides a comprehensive view of the Canadian equity market.

Canadian Dollar (CAD): The official currency of Canada, used for transactions and trade within the country. The Canadian Dollar is also widely traded in international foreign exchange markets.

Bank of Canada: Canada's central bank responsible for monetary policy, currency issuance, and overall financial system stability. It plays a critical role in managing the country's economic and financial well-being.

Royal Bank of Canada (RBC): One of the largest and most prominent banks in Canada, offering a wide range of financial services to individuals, businesses, and institutions. RBC is a key player in the Canadian banking sector.

Canadian Government Bonds: Debt securities issued by the Canadian government to finance its operations and projects. These bonds are considered relatively safe investments and play a significant role in the country's capital markets.

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If you're interested in accessing Techsalerator's End-of-Day Pricing Data for Canada, please contact info@techsalerator.com with your specific requirements. Techsalerator will provide you with a customized quote based on the number of data fields and records you need. The dataset can be delivered within 24 hours, and ongoing access options can be discussed if needed.

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Data fields included:

Equity Ticker Symbol Equity Closing Price Bond Ticker Symbol Bond Closing Price Index Ticker Symbol Index Closing Price Date of Closing Price Equity Name Equity Volume Equity High Price Equity Low Price Equity Open Price Bond Name Bond Coupon Rate Bond Maturity Index Name Index Change Index Percent Change Exchange Currency Total Market Capitalization Dividend Yield Price-to-Earnings Ratio (P/E) ‍

Q&A:

1. How much does the End-of-Day Pricing Data cost in Canada ?

The cost of this dataset may vary depending on factors such as the number of data fields, the frequency of updates, and the total records count. For precise pricing details, it is recommended to directly consult with a Techsalerator Data specialist.

1. How complete is the End-of-Day Pricing Data coverage in Canada?

Techsalerator provides comprehensive coverage of End-of-Day Pricing Data for various financial instruments, including equities, bonds, and indices. Thedataset encompasses major companies and securities traded on Canada exchanges.

1. How does Techsalerator collect this data?

Techsalerator collects End-of-Day Pricing Data from reliable sources, including stock exchanges, financial news outlets, and other market data providers. Data is carefully curated to ensure accuracy and reliability.

1. Can I select specific financial instruments or multiple countries with Techsalerator's End-of-Day Pricing Data?

Techsalerator offers the flexibility to select specific financial instruments, such as equities, bonds, or indices, depending on your needs. While the dataset focuses on Botswana, Techsalerator also provides data for other countries and international markets.

1. How do I pay for this dataset?

Techsalerator accepts various payment methods, including credit cards, direct tran...

Toronto-Dominion Bank stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

Between February and April 2020, the value of H&R REIT's stocks decreased by 59.87 percent. Their stock price fell from 21.68 Canadian dollars to 8.40 Canadian dollars in this period. In contrast, the average loss on the Toronto Stock Exchange (TSX) was 19.18 percent for the same period, as the coronavirus outbreak in the end of 2019 had a significant impact on the real estate investment sector in Canada.

The New York Stock Exchange (NYSE) is the largest stock exchange in the world, with an equity market capitalization of almost 36 trillion U.S. dollars as of June 2025. The following three exchanges were the NASDAQ, PINK Exchange, and the Frankfurt Exchange. What is a stock exchange? A stock exchange is a marketplace where stockbrokers, traders, buyers, and sellers can trade in equities products. The largest exchanges have thousands of listed companies. These companies sell shares of their business, giving the general public the opportunity to invest in them. The oldest stock exchange worldwide is the Frankfurt Stock Exchange, founded in the late sixteenth century. Other functions of a stock exchange Since these are publicly traded companies, every firm listed on a stock exchange has had an initial public offering (IPO). The largest IPOs can raise billions of dollars in equity for the firm involved. Related to stock exchanges are derivatives exchanges, where stock options, futures contracts, and other derivatives can be traded.

Learn how trading crude oil on the Toronto Stock Exchange (TSX) can provide opportunities for investors to gain exposure to the energy industry and potentially benefit from the performance of oil-related companies. Understand the factors that influence crude oil stock prices on the TSX and the risks associated with commodity investing.

The TSX WTI is the Toronto Stock Exchange benchmark price for West Texas Intermediate crude oil. It serves as a reference point for the Canadian oil market and is influenced by various global and domestic factors. Monitoring the TSX WTI can help investors assess the performance of Canadian energy stocks and gain insights into the overall oil market.

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.

Toronto Dominion (TD) Stock: Navigating the Financial Landscape

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