Under Section 16 of the Securities Exchange Act of 1934, senior executives, directors, and large-block shareholders are required to make ongoing filings about their company stock holdings to report any changes. These filings are made on Form 3, Form 4, and Form 5 and submitted to SECs Electronic Data Gathering, Analysis, and Retrieval (EDGAR) system.

When there is a vast variety of metrics and tools available to gain market insight, Insider trading offers valuable clues to investors related to future share performance. We at Smart Insider provide global insider trading data and analysis on share transactions made by directors & senior staff in the shares of their own companies.

Monitoring all the insider trading activity is a huge task, we identify 'Smart Insiders' through specialist desktop and quantitative feeds that enable our clients to generate alpha.

Our experienced analyst team use quantitative and qualitative methods to identify the stocks most likely to outperform based on deep analysis of insider trades, and the insiders themselves. Using our easy-to-read derived data we help our clients better understand insider transactions activity to make informed investment decisions.

We provide full customization of reports delivered by desktop, through feeds, or alerts. Our quant clients can receive data in a variety of formats such as XML, XLSX or API via SFTP or Snowflake.

Sample dataset for Desktop Service has been provided with some proprietary fields concealed. Upon request, we can provide a detailed Quant sample.

Tags: Stock Market Data, Equity Market Data, Insider Transactions Data, Insider Trading Intelligence, Trading, Investment Management, Alternative Investment, Asset Management, Equity Research, Market Analysis, United Kingdom, Europe

When there is a vast variety of metrics and tools available to gain market insight, Insider trading offers valuable clues to investors related to future share performance. We at Smart Insider provide global insider trading data and analysis on share transactions made by directors & senior staff in the shares of their own companies.

Monitoring all the insider trading activity is a huge task, we identify 'Smart Insiders' through specialist desktop and quantitative feeds that enable our clients to generate alpha.

Our experienced analyst team uses quantitative and qualitative methods to identify the stocks most likely to outperform based on deep analysis of insider trades, and the insiders themselves. Using our easy-to-read derived data we help our clients better understand insider transactions activity to make informed investment decisions.

We provide full customization of reports delivered by desktop, through feeds, or alerts. Our quant clients can receive data in a variety of formats such as XML, XLSX or API via SFTP or Snowflake.

Sample dataset for Desktop Service has been provided with some proprietary fields concealed. Upon request, we can provide a detailed Quant sample.

Tags: Stock Market Data, Equity Market Data, Insider Transactions Data, Insider Trading Intelligence, Trading Data, Investment Management, Alternative Investment, Asset Management, Equity Research, Market Analysis, Africa

The dataset consists of 644,643 corporate insider transactions between January 1986 and December 2013 that were filed to the Securities and Exchange Commission using Form 4 under Section 16 of the Securities Exchange Act of 1934. The original filings contain information on the identity of the trader, the role within the firm, the number of shares that were bought or sold, the transaction price, the total share position of the respective trader, the date of trade, and the date of reporting. The data on trades are merged with other characteristics of the insider or the firm. The dataset is used to investigate insider trading quantities and dollar profits to measure the benefits that insiders extract from their superior information. We describe and quantify the dollar profits, study the relation between trading returns and trading quantities and explore the determinants behind this relation.

By using this dataset, you agree to cite the Related Publication shown below. This dataset captures insider trading activity at publicly traded companies. The Securities and Exchange Commission has made these insider trading reports available on its web site in a structured format since mid-2003. However, most academic papers use proprietary commercial databases instead of regulatory filings directly, which makes replication challenging because the data manipulation and aggregation steps in commercial databases are opaque and historical records could be altered by the data provider over time. To overcome these limitations, the presented dataset is created from the original regulatory filings; it is updated daily and includes all information reported by insiders without alteration. Daily updates: https://dx.doi.org/10.34740/kaggle/ds/2973477

The insider trades made by corporate executives, directors and officers includes the purchases, sales and ownership of securities at a company. The insider transactions data is reliable as it is sourced directly from SEC forms 3,4 and 5. Insider trades is a valuable tool in stock trading and investing. The data on insider transactions is automatically updated once disclosures and reports are made available on SEC. In case you want to learn more about Finnworlds Insider Transactions API, please, visit the website. https://finnworlds.com/insider-transactions-api/

Get real-time insider trading data, Form 4 & Form 144 filings, and analytics from The Washington Service. Stay informed with expert insights.

Eight data sets that differ in whether they are used to predict investor trading in the same or subsequent periods with observations about the trading of neighbors in the social network. The periods are either daily or weekly windows. Moreover, we investigate separately investor influence over purchase and sale transactions. These three differences lead to eight distinct data sets. The size of the data sets ranges from just below 2,400 to almost 22 thousand observations. The labels are positive (set equal to 1) if an investor on a given day traded specific security in the same direction as at least one of his neighbors and negative (set equal to 0) otherwise. We use a sliding window with the size corresponding to the prediction window. In each window, for each ego investor, we create observations of instances of social influence in the neighborhood, given that at least one of the neighbors is active. An ego investor can be understood as a tippee and her neighbors as tippers. We record the specific behavior of investors in their neighborhood and, depending on the prediction period, the ego investors' behavior in the same or subsequent period. Initially, the data sets were highly imbalanced in terms of labels and, for this reason, were re-sampled to achieve a 1:3 label balance ratio.

Under Section 16 of the Securities Exchange Act of 1934, senior executives, directors, and large-block shareholders are required to make ongoing filings about their company stock holdings to report any changes. These filings are made on Form 3, Form 4, and Form 5 and submitted to SECs Electronic Data Gathering, Analysis, and Retrieval (EDGAR) system.

This dataset contains the raw experimental data and the analysis script for the paper Merl, R., Stöckl, T., Palan, S., 2022. "Insider trading regulation and shorting constraints. Evaluating the joint effects of two market interventions", Journal of Banking and Finance 106490, https://doi.org/10.1016/j.jbankfin.2022.106490.

Instructions:

1. Unpack all files into one folder.
2. Open R version 4.1.2 and set the working directory to the folder with all the files.
3. Run Script.R.

In case the SPTools package is not available from GitHub anymore, you can also find it included in this dataset so you can install it from here.

Smart Insider’s Global Share Buyback Database offers invaluable insights to investors on corporate actions data. We provide detailed, up-to-date share buyback data covering over 55,000 companies globally and over 20K+ from Asia, that’s every company that reports Buybacks through regulatory processes.

Our Share buyback data includes detailed information on all major buyback transactions including source announcements and derived analysis fields. Our platform adds a visual representation of the data, allowing investors to quickly identify patterns and make decisions based on their findings.

Get detailed share buyback insights with Smart Insider and stay ahead of the curve with accurate, historical buyback insight that helps you make better investment decisions.

We provide full customization of reports delivered by desktop, through feeds, or alerts. Our quant clients can receive data in a variety of formats such as CSV, XML or XLSX via SFTP, API or Snowflake.

Sample dataset for Desktop Service has been provided with limited fields. Upon request, we can provide a detailed Quant sample.

Tags: Equity Market Data, Stock Market Data, Corporate Actions Data, Corporate Buyback Data, Company Financial Data, Insider Trading Data

Smart Insider’s Global Share Buyback Database offers invaluable insights to investors on stock market data. We provide detailed, up-to-date share buyback data covering over 55,000 companies globally and over 8,000+ in Europe & UK, that’s every company that reports Buybacks through regulatory processes.

Our Share buyback data includes detailed information on all major buyback transactions including source announcements and derived analysis fields. Our platform adds a visual representation of the data, allowing investors to quickly identify patterns and make decisions based on their findings.

Get detailed share buyback insights with Smart Insider and stay ahead of the curve with accurate, historical buyback insight that helps you make better investment decisions.

We provide full customization of reports delivered by desktop, through feeds, or alerts. Our quant clients can receive data in a variety of formats such as CSV, XML or XLSX via SFTP, API or Snowflake.

Sample dataset for Desktop Service has been provided with limited fields. Upon request, we can provide a detailed Quant sample.

Tags: Equity Market Data, Stock Market Data, Corporate Actions Data, Corporate Buyback Data, Company Financial Data, Insider Trading Data

Smart Insider’s Global Share Buyback Database offers invaluable insights to investors. We provide detailed, up-to-date share buyback data covering over 55,000 companies globally and over 12,200 from US & Canada (North America), that’s every company that reports Buybacks through regulatory processes.

Our Share buyback data includes detailed information on all major buyback transactions including source announcements and derived analysis fields. Our platform adds a visual representation of the data, allowing investors to quickly identify patterns and make decisions based on their findings.

Get detailed share buyback insights with Smart Insider and stay ahead of the curve with accurate, historical buyback insight that helps you make better investment decisions.

We provide full customization of reports delivered by desktop, through feeds, or alerts. Our quant clients can receive data in a variety of formats such as CSV, XML or XLSX via SFTP, API or Snowflake.

Sample dataset for Desktop Service has been provided with limited fields. Upon request, we can provide a detailed Quant sample.

Tags: Equity Market Data, Stock Market Data, Corporate Actions Data, Corporate Buyback Data, Company Financial Data, Insider Trading Data

Snapshot img

Trade Surveillance Systems Market Size 2025-2029

The trade surveillance systems market size is forecast to increase by USD 2.53 billion, at a CAGR of 29.7% between 2024 and 2029.

The market is witnessing significant growth due to the increasing demand for comprehensive 360-degree trade surveillance. With the financial industry's heightened focus on preventing criminal and fraudulent trading activities, predictive monitoring solutions have become essential. These systems enable real-time analysis of trading data, identifying potential risks and anomalies before they escalate into significant issues. However, the implementation of these systems comes with challenges. Infrastructural requirements, including the integration of various data sources and the need for advanced technology, pose significant obstacles. Additionally, ensuring regulatory compliance and maintaining data security are ongoing concerns. Companies must navigate these challenges while also staying abreast of evolving regulatory requirements and market trends to effectively capitalize on the opportunities presented by the growing demand for robust trade surveillance solutions.

What will be the Size of the Trade Surveillance Systems Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free SampleThe market continues to evolve, driven by the dynamic nature of financial markets and the need for advanced technologies to ensure regulatory compliance and prevent financial crimes. These systems are integral to risk management in various sectors, including investment banks, brokerage firms, hedge funds, and asset management companies. Deep learning, automated investigations, fraud detection, order book analysis, algorithmic surveillance, and artificial intelligence are seamlessly integrated into these systems to detect suspicious activity, insider trading, market manipulation, and price anomalies in real-time. Market surveillance solutions employ machine learning models and natural language processing to analyze vast amounts of data from securities trading, derivatives trading, and market data integration. Cloud computing and data visualization tools facilitate efficient data storage and analysis, while reporting tools and regulatory reporting ensure transparency and compliance with regulatory requirements. Market abuse prevention and data security are paramount, with alerting systems and system integration providing real-time alerts for potential threats. The ongoing unfolding of market activities and evolving patterns necessitate continuous innovation and adaptation in trade surveillance systems. These systems are essential in safeguarding the integrity of financial markets and maintaining investor confidence.

How is this Trade Surveillance Systems Industry segmented?

The trade surveillance systems industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. ComponentSolutionsServicesDeploymentOn-premisesCloud-basedSectorLarge enterprisesSmall and medium enterprisesApplicationBanksInstitutional brokersRetail brokersGeographyNorth AmericaUSCanadaEuropeFranceGermanyItalyUKAPACChinaIndiaJapanSouth KoreaRest of World (ROW).

By Component Insights

The solutions segment is estimated to witness significant growth during the forecast period.The market is experiencing significant growth due to the increasing focus on risk management, regulatory compliance, and financial crime prevention in financial markets. Investment banks and brokerage firms are implementing advanced solutions to detect suspicious activity, insider trading, market manipulation, and price anomalies in real-time. Cloud computing and machine learning models are driving the adoption of automated investigations, algorithmic surveillance, and deep learning technologies. SaaS-based solutions for trade surveillance systems are gaining popularity due to their ease of use, low total cost of ownership, and cost-effectiveness. End-users, including institutional brokers and sectors such as BFSI and healthcare, are demanding integrated trade surveillance software that offers data visualization, transaction analytics, and market data integration. Regulatory reporting and compliance auditing are also critical factors driving the market's growth. Moreover, the increasing use of artificial intelligence, natural language processing, and system integration is enabling advanced trading pattern recognition and market abuse prevention. Derivatives trading and hedge funds are also adopting trade surveillance systems to manage risk and ensure regulatory compliance. Data security and data storage are essential considerations for market participan

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.

Elon Musk Accused of Insider Trading in Dogecoin Lawsuit

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

Smart Insider’s Global Share Buyback Database offers invaluable insights to investors on public equity market data. We provide detailed, up-to-date share buyback data covering over 55,000 companies globally including Africa, that’s every company that reports Buybacks through regulatory processes.

Our Share buyback data includes detailed information on all major buyback transactions including source announcements and derived analysis fields. Our platform adds a visual representation of the data, allowing investors to quickly identify patterns and make decisions based on their findings.

Get detailed share buyback insights with Smart Insider and stay ahead of the curve with accurate, historical buyback insight that helps you make better investment decisions.

We provide full customization of reports delivered by desktop, through feeds, or alerts. Our quant clients can receive data in a variety of formats such as CSV, XML or XLSX via SFTP, API or Snowflake.

Sample dataset for Desktop Service has been provided with limited fields. Upon request, we can provide a detailed Quant sample.

Tags: Equity Market Data, Stock Market Data, Corporate Actions Data, Corporate Buyback Data, Company Financial Data, Insider Trading Data, Africa

The Trade Surveillance Systems market is an essential component of contemporary financial infrastructure, designed to safeguard against market manipulations, insider trading, and other unethical trading practices. These systems analyze trading data, identify suspicious activities, and ensure compliance with regulato

Comprehensive financial analysis and data for TW including insider trading, institutional holdings, and key metrics.

In recent years, the Trade Surveillance Software market has emerged as a critical component for financial institutions aiming to maintain compliance with complex regulatory environments and guard against market abuses like insider trading and market manipulation. This software facilitates the real-time monitoring of

API providing data for top institutional holders, mutual fund holders, and insider transactions.