The main stock market index of United States, the US500, fell to 6369 points on March 27, 2026, losing 1.67% from the previous session. Over the past month, the index has declined 7.45%, though it remains 14.12% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on March of 2026.

Stock Charts

This dataset is a collection of a sample of images from tweets that I scraped using my Discord bot that keeps track of financial influencers on Twitter. The data consists of images that were part of tweets that mentioned a stock. This dataset can be used for a wide variety of tasks, such as image classification or feature extraction.

  FinTwit Charts Collection

This dataset is part of a larger collection of datasets, scraped from Twitter and labeled by a… See the full description on the dataset page: https://huggingface.co/datasets/StephanAkkerman/stock-charts.

The main stock market index of United States, the US500, fell to 6359 points on March 27, 2026, losing 1.82% from the previous session. Over the past month, the index has declined 7.59%, though it remains 13.95% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on March of 2026.

Stock Chart

## Overview

Stock Chart is a dataset for object detection tasks - it contains Stocks annotations for 80 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Graph and download economic data for Index of Common Stock Prices, New York Stock Exchange for United States (M11007USM322NNBR) from Jan 1902 to May 1923 about stock market, New York, indexes, and USA.

Context

This dataset provides synthetically generated financial time series data, presented as OHLCV (Open-High-Low-Close-Volume) candlestick charts. A key feature of this dataset is the inclusion of technical analysis annotations (labels) meticulously created by a human analyst for each chart.

The primary goal is to offer a resource for training and evaluating machine learning models focused on automated technical analysis and chart pattern recognition. By providing synthetic data with high-quality human labels, this dataset aims to facilitate research and development in areas like algorithmic trading and financial visualization analysis.

This is an evolving dataset. It represents the initial phase of a larger labeling effort, and future updates are planned to incorporate a greater number and variety of labeled chart patterns.

Content

The dataset is provided entirely as a collection of JSON files. Each file represents a single 300-candle chart window and contains:

1. metadata: Contains basic information related to the generation of the file (e.g., generation timestamp, version).
2. ohlcv_data: A sequence of 300 data points. Each point is a dictionary representing one time candle and includes:
   • time: Timestamp string (ISO 8601 format). Note: These timestamps maintain realistic intra-day time progression (hours, minutes), but the specific dates (Day, Month, Year) are entirely synthetic and do not align with real-world calendar dates.
   • open, high, low, close: Numerical values representing the candle's price range. Note: These values are synthetic and are not tied to any real financial instrument's price.
   • volume: A numerical value representing activity during the candle's period. Note: This is also a synthetic value.
3. labels: A dictionary containing the human-provided technical analysis annotations for the corresponding chart window:
   • horizontal_lines: A list of structures, each containing a price key. These typically denote significant horizontal levels identified by the labeler, such as support or resistance.
   • ray_lines: A list of structures, each defining a line segment via start_date, start_price, end_date, and end_price. These are used to represent patterns like trendlines, channel boundaries, or other linear formations observed by the labeler.

Data Generation Approach

The dataset features synthetically generated candlestick patterns. The generation process focuses on creating structurally plausible chart sequences. Human analysts then carefully review these sequences and apply relevant technical analysis labels (support, resistance, trendlines).

While the patterns may resemble those seen in financial markets, the underlying numerical data (price, volume, and the associated timestamps) is artificial and intentionally detached from any real-world financial data. Users should focus on the relative structure of the candles and the associated human-provided labels, rather than interpreting the absolute values as representative of any specific market or time.

Acknowledgements

This dataset is made possible through ongoing human labeling efforts and custom data generation software.

Inspiration

• Train models (e.g., CNNs, Transformers) to recognize support/resistance levels and trendlines directly from chart data.
• Develop and benchmark algorithms for automated technical analysis pattern detection.
• Use as a basis for generating further augmented chart data for ML training.
• Explore novel approaches to financial time series analysis using labeled, synthetic data.

Greece's main stock market index, the Athens General, fell to 2024 points on March 27, 2026, losing 1.74% from the previous session. Over the past month, the index has declined 8.02%, though it remains 16.63% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Greece. Greece Stock Market (ASE) - values, historical data, forecasts and news - updated on March of 2026.

Germany's main stock market index, the DE40, fell to 22301 points on March 27, 2026, losing 1.38% from the previous session. Over the past month, the index has declined 9.49% and is down 0.72% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Germany. Germany Stock Market Index (DE40) - values, historical data, forecasts and news - updated on March of 2026.

Literature on stock price prediction.

Experimental parameter settings.

Graph and download economic data for Index of Stock Prices for Germany (M1123ADEM324NNBR) from Jan 1870 to Dec 1913 about stock market, Germany, and indexes.

ABSTRACT This article aims to analyze the shares that make up the Brazilian IBRX100 index, verifying which sectors had the greatest influence on the Stock Exchange in 2018, 2019, and 2020. For this purpose, the theory of graph centrality measures was used to discover the most central shares. A balance analysis of the graphs was also performed, since balanced graphs are more stable, generating a more predictable stock portfolio. This study may help investors to compose a safer stock portfolio and identify which stocks are most correlated with each other. The most central shares can aid in perceiving stock market trends.

Financial Knowledge Graph Dataset Introduction

Dataset Overview

The directory /Users/zhangtao/Trae_Project/ShowKnowledge-main/data/knowledge/ contains a comprehensive financial knowledge graph dataset focusing on stock market information. This dataset consists of multiple CSV files covering relationships between stocks, concepts, and shareholders, providing a rich data foundation for knowledge graph construction and analysis in the financial domain.

Dataset File Structure

The dataset includes the following main files: - 概念信息.csv (Concept Information): Contains coding, names, and sources of stock concepts - 股东信息.csv (Shareholder Information): Records detailed information about company shareholders - 股票-概念信息.csv (Stock-Concept Relationship): Associations between stocks and concepts - 股票-股东信息.csv (Stock-Shareholder Relationship): Associations between stocks and shareholders - 股票信息.csv, 股票信息1.csv, and 股票信息-全.csv (Stock Information): Basic and detailed data about stocks

Data Content Details

Concept Information

The 概念信息.csv file contains classification information for various stock concepts in the market. Each concept has a unique code (such as TS0, TS1, etc.), concept name (such as "Integrated Circuits", "Beibu Gulf New Area", etc.), and data source identifier. These concepts are important references for analyzing stock sectors and industry trends.

Shareholder Information

The 股东信息.csv file records the shareholder information of listed companies, including individual shareholders and institutional shareholders. The data shows the characteristics of the equity structure in China's capital market, including various types of shareholders such as state-owned enterprises, private enterprises, investment funds, and individual investors.

Stock Relationship Data

The 股票-概念信息.csv and 股票-股东信息.csv establish the relationships between stocks and concepts, and between stocks and shareholders. These relationships are the core edge data for constructing knowledge graphs, enabling the system to perform complex relationship queries and analyses.

Dataset Application Value

1. Financial Analysis: Can be used to analyze stock market structure, equity distribution, and concept sector relationships
2. Knowledge Graph Research: Provides real data for the construction of knowledge graphs in the financial field
3. Investment Decision Support: Assists investment decisions through analysis of shareholder structures and concept associations
4. Market Regulation Reference: Provides data support for market structure and relationships for regulatory agencies
5. Academic Research: Supports academic research in fields such as financial market structure and corporate governance

Data Characteristics

1. Comprehensiveness: Covers three core entities—stocks, concepts, and shareholders—and their relationships
2. Structure: Uses CSV format for easy data processing and import into graph databases
3. Connectivity: Supports complex graph queries through relationships between entities
4. Practicality: Data sourced from the real market, with practical application value

China's main stock market index, the SHANGHAI, rose to 3914 points on March 27, 2026, gaining 0.63% from the previous session. Over the past month, the index has declined 6.43%, though it remains 16.78% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from China. China Shanghai Composite Stock Market Index - values, historical data, forecasts and news - updated on March of 2026.

This is a dataset containing stock chart patterns images for the upcoming trend is uptrend or downtred. It is used for classification of stock chart patterns as it will become uptrend or downtred.

The value of the DJIA index amounted to ********* at the end of February 2026, up from ********* at the end of March 2020. Global panic about the coronavirus epidemic caused the drop in March 2020, which was the worst drop since the collapse of Lehman Brothers in 2008. Dow Jones Industrial Average index – additional information The Dow Jones Industrial Average index is a price-weighted average of 30 of the largest American publicly traded companies on New York Stock Exchange and NASDAQ, and includes companies like Goldman Sachs, IBM and Walt Disney. This index is considered to be a barometer of the state of the American economy. DJIA index was created in 1986 by Charles Dow. Along with the NASDAQ 100 and S&P 500 indices, it is amongst the most well-known and used stock indexes in the world. The year that the 2018 financial crisis unfolded was one of the worst years of the Dow. It was also in 2008 that some of the largest ever recorded losses of the Dow Jones Index based on single-day points were registered. On September 29, 2008, for instance, the Dow had a loss of ****** points, one of the largest single-day losses of all times. The best years in the history of the index still are 1915, when the index value increased by ***** percent in one year, and 1933, year when the index registered a growth of ***** percent.

The Dow Jones Industrial Average (DJIA) index dropped around ***** points in the four weeks from February 12 to March 11, 2020, but has since recovered and peaked at ********* points as of November 24, 2024. In February 2020 - just prior to the global coronavirus (COVID-19) pandemic, the DJIA index stood at a little over ****** points. U.S. markets suffer as virus spreads The COVID-19 pandemic triggered a turbulent period for stock markets – the S&P 500 and Nasdaq Composite also recorded dramatic drops. At the start of February, some analysts remained optimistic that the outbreak would ease. However, the increased spread of the virus started to hit investor confidence, prompting a record plunge in the stock markets. The Dow dropped by more than ***** points in the week from February 21 to February 28, which was a fall of **** percent – its worst percentage loss in a week since October 2008. Stock markets offer valuable economic insights The Dow Jones Industrial Average is a stock market index that monitors the share prices of the 30 largest companies in the United States. By studying the performance of the listed companies, analysts can gauge the strength of the domestic economy. If investors are confident in a company’s future, they will buy its stocks. The uncertainty of the coronavirus sparked fears of an economic crisis, and many traders decided that investment during the pandemic was too risky.

Stock market index in Mexico, February, 2026 The most recent value is 161.03 points as of February 2026, an increase compared to the previous value of 152.59 points. Historically, the average for Mexico from January 1970 to February 2026 is 37.25 points. The minimum of 0 points was recorded in January 1970, while the maximum of 161.03 points was reached in February 2026. | TheGlobalEconomy.com

Hong Kong's main stock market index, the HK50, fell to 24706 points on March 27, 2026, losing 0.61% from the previous session. Over the past month, the index has declined 5.20%, though it remains 5.46% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Hong Kong. Hong Kong Stock Market Index (HK50) - values, historical data, forecasts and news - updated on March of 2026.

View data of the S&P 500, an index of the stocks of 500 leading companies in the US economy, which provides a gauge of the U.S. equity market.