Singapore's main stock market index, the STI, fell to 4356 points on October 16, 2025, losing 0.28% from the previous session. Over the past month, the index has climbed 0.75% and is up 20.16% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Singapore. Singapore Stock Market (STI) - values, historical data, forecasts and news - updated on October of 2025.

Explore LSEG's Singapore Stock Exchange data, offering information across key segments including Equities and Fixed Income, Derivatives, and Corporate.

Stock market return (%, year-on-year) in Singapore was reported at 14.65 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Singapore - Stock market return (%, year-on-year) - actual values, historical data, forecasts and projections were sourced from the World Bank on October of 2025.

Key information about Singapore FTSE Strait Times

• Singapore FTSE Strait Times closed at 3,895.7 points in Feb 2025, compared with 3,855.8 points at the previous month end
• Singapore Equity Market Index: Month End: FTSE Strait Times data is updated monthly, available from Jan 1985 to Feb 2025, with an average number of 2,122.9 points
• The data reached an all-time high of 3,895.7 points in Feb 2025 and a record low of 465.1 points in Apr 1986

• In the latest reports, FTSE All Share recorded a monthly P/E ratio of 13.2 in Jun 2022

Stock market total value traded to GDP (%) in Singapore was reported at 30.42 % in 2019, according to the World Bank collection of development indicators, compiled from officially recognized sources. Singapore - Stock market total value traded to GDP - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2025.

Stock market turnover ratio (%) in Singapore was reported at 16.38 % in 2019, according to the World Bank collection of development indicators, compiled from officially recognized sources. Singapore - Stock market turnover ratio - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2025.

Graph and download economic data for Stock Market Total Value Traded to GDP for Singapore (DDDM02SGA156NWDB) from 1979 to 2019 about Singapore, market cap, stock market, trade, and GDP.

Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_6dd4e62cb6a4c648bb2f72f8d6672552/view

Singapore SGX: Market Capitalisation: Total data was reported at 974,797.200 SGD mn in Sep 2018. This records an increase from the previous number of 970,051.700 SGD mn for Aug 2018. Singapore SGX: Market Capitalisation: Total data is updated monthly, averaging 661,983.700 SGD mn from Jan 1999 (Median) to Sep 2018, with 237 observations. The data reached an all-time high of 1,073,673.600 SGD mn in Jan 2018 and a record low of 273,339.000 SGD mn in Jan 1999. Singapore SGX: Market Capitalisation: Total data remains active status in CEIC and is reported by Monetary Authority of Singapore. The data is categorized under Global Database’s Singapore – Table SG.Z017: Singapore Exchange Securities Trading Limited (SGX-ST): Market Capitalisation.

Graph and download economic data for Volatility of Stock Price Index for Singapore (DDSM01SGA066NWDB) from 2000 to 2021 about Singapore, stocks, volatility, price index, indexes, and price.

Singapore: Stock market capitalization as percent of GDP: The latest value from 2024 is 116.49 percent, a decline from 120.35 percent in 2023. In comparison, the world average is 69.42 percent, based on data from 67 countries. Historically, the average for Singapore from 1979 to 2024 is 163.7 percent. The minimum value, 57.78 percent, was reached in 1985 while the maximum of 297.98 percent was recorded in 2007.

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

Singapore SG: Stocks Traded: Total Value data was reported at 219.612 USD bn in 2017. This records an increase from the previous number of 188.052 USD bn for 2016. Singapore SG: Stocks Traded: Total Value data is updated yearly, averaging 74.137 USD bn from Dec 1979 (Median) to 2017, with 39 observations. The data reached an all-time high of 381.289 USD bn in 2007 and a record low of 1.063 USD bn in 1979. Singapore SG: Stocks Traded: Total Value data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Singapore – Table SG.World Bank.WDI: Financial Sector. The value of shares traded is the total number of shares traded, both domestic and foreign, multiplied by their respective matching prices. Figures are single counted (only one side of the transaction is considered). Companies admitted to listing and admitted to trading are included in the data. Data are end of year values converted to U.S. dollars using corresponding year-end foreign exchange rates.; ; World Federation of Exchanges database.; Sum; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

Singapore: Stock market turnover ratio: The latest value from 2019 is 16.38 percent, a decline from 31.94 percent in 2018. In comparison, the world average is 25.58 percent, based on data from 73 countries. Historically, the average for Singapore from 1979 to 2019 is 42.43 percent. The minimum value, 7.81 percent, was reached in 1979 while the maximum of 95.49 percent was recorded in 2008.

Singapore Stock Symbols & Company Metadata

This dataset contains stock symbols and basic company metadata for all listed companies in Singapore.It is updated weekly if new changes are there.

  📊 Dataset Contents

The dataset is provided as a CSV file with the following columns:

Column Description

name Full company name

ticker Stock ticker symbol (e.g., AAPL, MSFT)

market The exchange/market where the stock is listed

sector The primary business sector of… See the full description on the dataset page: https://huggingface.co/datasets/ThunderDrag/Singapore-Stock-Symbols-and-Metadata.

Graph and download economic data for Market Capitalization Outside of Top 10 Largest Companies to Total Market Capitalization for Singapore (DDAM02SGA156NWDB) from 1998 to 2017 about Singapore, market cap, companies, and stock market.

Singapore SG: Stocks Traded: Total Value: % of GDP data was reported at 67.801 % in 2017. This records an increase from the previous number of 60.708 % for 2016. Singapore SG: Stocks Traded: Total Value: % of GDP data is updated yearly, averaging 68.266 % from Dec 1979 (Median) to 2017, with 39 observations. The data reached an all-time high of 211.849 % in 2007 and a record low of 7.553 % in 1985. Singapore SG: Stocks Traded: Total Value: % of GDP data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Singapore – Table SG.World Bank.WDI: Financial Sector. The value of shares traded is the total number of shares traded, both domestic and foreign, multiplied by their respective matching prices. Figures are single counted (only one side of the transaction is considered). Companies admitted to listing and admitted to trading are included in the data. Data are end of year values.; ; World Federation of Exchanges database.; Weighted average; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

Stock market capitalization to GDP (%) in Singapore was reported at 189 % in 2020, according to the World Bank collection of development indicators, compiled from officially recognized sources. Singapore - Stock market capitalization to GDP - actual values, historical data, forecasts and projections were sourced from the World Bank on October 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.

Sweet Rewards: Is SG Stock a Good Investment?

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