The data was collected via '*pandas.read_html()*' and, it refers to all transactions between 13-12-2021 and 22-12-2021 (DD-MM-YY). This data set is the first version.

Source: http://openinsider.com/

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.

Historical SEC dataset containing all insider transactions (Form 4 filings). The data is public, and sourced from the SEC's EDGAR database out of their XML filings. Lightly processed for easier consumption. All Form 4 filings from Jan/20 to Jun/25

Why this exists

Form 4s are noisy to work with: amended filings, multiple insiders per transaction, and inconsistent tables. This dataset provides clean, normalized insider-transaction data with a stable schema so you can backtest signals and monitor insider activity without scraping.

What you get:

• Company (name, ticker if known), CIK
• Insider(s) with role (Director/Officer/10% Owner, etc.)
• Trade details: transaction date, type, number of shares, price, total consideration
• Holdings before/after the transaction

Update cadence: monthly (moving to daily as we scale). Source: U.S. SEC EDGAR Form 4 filings.

We're building a real-time API for new filings with clean JSON endpoints and low latency. If interested, sign up to our waiting list: 👉 https://secfilingapi.com/?utm_source=kaggle&utm_medium=dataset&utm_campaign=form4

Ideas to try with the data:

• Event study: top-decile insider buys vs sector ETF over 30/60/90 days
• Cluster insiders by role + transaction size; test persistence
• Filter for CEO buys after 20% drawdowns (momentum/contrarian mix)
• Find unusual clusters (multiple insiders buying within 10 days)

Limitations & notes:

• There are a few missing filings in the historical data (< 1000 total, all very old filings, before the SEC launched the XML format).
• Forms 4B (amendments to form 4 - rare - are not included)
• Mapping from CIK→ticker can lag for recent IPOs/SPACs.
• Always verify edge cases against the EDGAR link when publishing results.

Feedback & requests welcome in the Discussion tab.

DISCLAIMER: It is possible that inaccuracies or other errors were introduced into the data sets during the process of extracting the data and compiling the data sets. The data set is intended to assist the public in analyzing data contained in Commission filings; however, they are not a substitute for such filings. Investors should review the full Commission filings before making any investment decision.

Insider trading is the buying or selling of a security by someone who has access to material nonpublic information about the security. Insider trading can be illegal or legal depending on when the insider makes the trade. It is illegal when the material information is still nonpublic.

However, it is not illegal to own, or buy and sell shares of the company you work for, as long as the transactions are being disclosed publicly in a timely manner and as long as the information that is being used to trade is publicly available. The Securities and Exchange Commission has rules to protect investments from the effects of insider trading. The SEC has prosecuted insider trading cases against Directors, officers and employees of involved corporations as well as tepees.

When a corporate insider buys or sells his company's security this trading activity must be reported to the SEC, which then discloses this information to the public .Even though the trading is disclosed, Corporate Insiders can only trade their Corporation's Securities during certain windows of time when there is no material non-public information that might affect a buyer or seller's trading decision. In this blog post I present the result of my Insider Trading Analysis , the code for which can be found in this repository.

I've scraped 30,000 rows of data from Insidertrading.org for the time period August 18 2016 to December 26 2017. This data contains features such as Transaction Date, Company Name, Company Stock Symbol, Insider Name, Transaction Volume, Price Per share etc. Since the data didn't have the industry to which a company belongs to I matched up the Industry dataset from NASDAQ to the stock symbols in the above data

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.

For researchers and developers, this dataset provides a transparent, reproducible source of insider trading data.

For practitioners and retail investors seeking real-time alerts derived from the same underlying regulatory filings, see Ebomi at https://ebomi.com, a live service built directly on this work.

By using this dataset or accompanying code, you agree to cite both the data source and the related publication.

Balogh, A. Layline Insider Trading Dataset. Harvard Dataverse https://doi.org/10.7910/DVN/VH6GVH (2023).

Balogh, A. Insider trading. Scientific Data 10, 237, https://doi.org/10.1038/s41597-023-02147-6 (2023).

Dara was scraped from openinsider.com which in turn was scraped from finviz.com 🙂

Pull recent SEC Form 4 insider transactions for a list of U.S. tickers, compute % of shares outstanding, build buy/sell summaries with conditional highlighting, and optionally flag open-**market notional spikes **using free data (Yahoo Finance) so anyone can run it without paid APIs.

!!! Not financial advice. Data may be delayed/incorrect. Always verify with the original filings. !!!

What you get

Sheets in Excel output:- form4 sale – all insider sells (per transaction) form4 buy – open-market insider buys (code P) summary sales – grouped by ticker + company with totals (total_pct_outstanding = sum of per-filing % of common shares outstanding) summary buy – grouped by ticker + company with totals open market spikes (free) – unusual daily notional bars (price × volume) from Yahoo Finance (no key required)

Significate Highlights

Per-row Large/Medium/Small flags (editable thresholds in form4_config.json) **Bullish (summary buy) rows highlighted green **when total % ≥ threshold Bearish (summary sales) rows highlighted red when total % ≥ threshold

A snapshot of sample table with data:- https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F29334708%2F58431b22fb49dcd66753c0642a572fdf%2Fsample.png?generation=1760339565401762&alt=media" alt="">

This dataset contains a comprehensive analysis of insider trading patterns derived from SEC Form 4 filings. The project explores various aspects of insider trading behavior, including:

1. Data preprocessing and exploration of over 500,000 insider trading entries
2. In-depth analysis of transaction volumes, buy vs. sell patterns, and top insiders and companies
3. Time series analysis of trading volumes, including moving averages and seasonal patterns
4. Sector-wise breakdown of insider trading activities
5. Detailed examination of transaction codes and their distributions
6. Investigation of the relationship between transaction size and stock price
7. Network analysis of insider trading relationships
8. Predictive modeling of stock price changes based on insider trading data

The analysis provides insights into the characteristics of insider trading, seasonal trends, and the predictive power of insider trading data for short-term stock price movements. This project combines data analysis, statistical methods, and machine learning techniques to offer a multifaceted view of insider trading behavior in the U.S. stock market.

The PDF file contains the full Jupyter notebook with code, visualizations, and detailed explanations of each analysis step."

This description gives potential readers an overview of what they can expect from your analysis, highlighting the key components and the depth of your work.

Communications Surveillance for Traders Market Outlook

According to our latest research, the global Communications Surveillance for Traders market size reached USD 1.92 billion in 2024, with a robust year-on-year growth trajectory. The market is experiencing a significant expansion, registering a CAGR of 15.4% from 2025 to 2033. By the end of 2033, the market is expected to attain a value of USD 6.16 billion, fueled by stringent regulatory requirements, increasing sophistication of trading activities, and a rising need for advanced surveillance solutions to mitigate risks and ensure compliance across financial institutions.

The primary growth driver for the Communications Surveillance for Traders market is the ever-tightening global regulatory landscape. Financial authorities worldwide, such as the SEC, FCA, and ESMA, have imposed rigorous compliance mandates to counteract insider trading, market abuse, and other illicit activities. These regulations necessitate robust surveillance frameworks capable of monitoring, analyzing, and archiving a vast array of communications—including emails, instant messages, voice calls, and social media interactions—across multiple channels. As trading environments become increasingly digitized and complex, organizations are compelled to invest in advanced surveillance technologies that leverage machine learning, natural language processing, and AI-driven analytics to detect anomalies and ensure regulatory adherence. This regulatory pressure is particularly acute for banks, brokerage firms, and asset management companies, which face substantial penalties for non-compliance, further accelerating market demand.

Another critical factor propelling market growth is the rapid evolution of trading platforms and the integration of multi-channel communication tools. The proliferation of electronic trading, algorithmic strategies, and decentralized finance has led to an exponential increase in trading volumes and the diversity of communication channels used by traders. Surveillance solutions must now monitor not only traditional voice and email but also chat platforms, mobile messaging, and collaboration tools such as Microsoft Teams and Slack. This complexity necessitates scalable and interoperable surveillance systems capable of aggregating and analyzing data from disparate sources in real time. The demand for such flexible, cloud-enabled solutions is rising, as they facilitate seamless integration with existing IT infrastructure and provide the agility required to adapt to evolving trading practices.

The market’s momentum is further sustained by the growing emphasis on risk management and fraud detection. Financial institutions are increasingly aware of the reputational and financial risks associated with undetected market abuse, collusion, or fraudulent activities. Advanced communications surveillance solutions, equipped with predictive analytics and behavioral monitoring, enable proactive identification of suspicious patterns and potential threats. By automating surveillance workflows and providing actionable insights, these solutions not only enhance compliance but also support broader risk management and operational resilience strategies. This dual benefit is particularly attractive to large enterprises and hedge funds managing high-value transactions and complex portfolios.

From a regional perspective, North America continues to dominate the Communications Surveillance for Traders market, accounting for the largest share in 2024. This leadership is attributed to the region’s mature financial sector, early adoption of digital trading technologies, and stringent regulatory environment. Europe follows closely, driven by MiFID II and MAR regulations, while Asia Pacific is witnessing the fastest growth, propelled by the expansion of electronic trading and increasing regulatory oversight in emerging markets. Latin America and the Middle East & Africa are gradually catching up, as local financial institutions recognize the importance of robust surveillance to attract global investors and mitigate cross-border risks. Overall, the global outlook is characterized by heightened investment in compliance infrastructure and a shift towards cloud-based, AI-powered surveillance platforms.

Trade Surveillance Software Market Outlook

As per our latest research, the global trade surveillance software market size in 2024 reached USD 1.82 billion, reflecting robust adoption across financial institutions and regulatory-driven sectors. The market is set to grow at a CAGR of 18.9% from 2025 to 2033, projecting to achieve a value of USD 9.84 billion by 2033. This rapid expansion is fueled by escalating regulatory compliance requirements, increasing sophistication of financial crimes, and the proliferation of digital trading platforms globally. The demand for advanced trade surveillance solutions is intensifying as organizations strive to ensure transparency, mitigate risks, and safeguard market integrity in an evolving regulatory landscape.

One of the primary growth drivers for the trade surveillance software market is the surge in regulatory mandates imposed by global financial authorities. Regulatory bodies such as the SEC, ESMA, and FCA are introducing stringent guidelines to prevent market manipulation, insider trading, and other illicit trading activities. These evolving regulations compel financial institutions to adopt robust surveillance systems capable of real-time monitoring and analytics. The need for automated, scalable, and integrated solutions is rising as manual monitoring becomes increasingly impractical due to the volume and complexity of trades. As a result, organizations are investing heavily in advanced trade surveillance software to ensure compliance, avoid hefty penalties, and maintain their reputational standing in the market.

Technological advancements are significantly shaping the trajectory of the trade surveillance software market. The integration of artificial intelligence, machine learning, and big data analytics into surveillance platforms has enabled more accurate detection of anomalous trading patterns and potential fraud. These technologies empower organizations to process vast amounts of data in real-time, identify subtle trends, and generate actionable insights for compliance teams. Furthermore, the adoption of cloud-based solutions is accelerating, offering scalability, cost efficiency, and enhanced collaboration across geographically dispersed teams. As trading volumes and data complexity continue to rise, the reliance on intelligent, automated surveillance tools is expected to intensify, further propelling market expansion.

The increasing prevalence of digital trading and algorithmic trading strategies is another pivotal factor contributing to the growth of the trade surveillance software market. With the proliferation of electronic trading platforms, financial markets are witnessing heightened risks of market abuse and manipulation. Trade surveillance software plays a critical role in monitoring high-frequency trades, cross-asset transactions, and complex derivatives. The ability to provide holistic surveillance across multiple asset classes and jurisdictions is becoming a key differentiator for solution providers. As digital transformation accelerates within the financial sector, the demand for comprehensive, agile, and customizable surveillance solutions is expected to surge, driving sustained market growth through the forecast period.

Regionally, North America continues to dominate the trade surveillance software market, accounting for the largest revenue share in 2024, followed by Europe and Asia Pacific. The region's leadership is attributed to the presence of major financial hubs, early adoption of advanced technologies, and a proactive regulatory environment. However, Asia Pacific is anticipated to exhibit the fastest growth rate over the forecast period, driven by rapid financial market development, increasing cross-border trading activities, and evolving regulatory frameworks. Latin America and the Middle East & Africa are also witnessing steady adoption, propelled by modernization initiatives and growing awareness of compliance requirements. The regional outlook underscores the global nature of trade surveillance challenges and the universal need for robust, scalable solutions.

Component Analysis

The trade surveillance software market by component is bifurcated into software and services, each playing a distinctive role in shaping the industry landscape. The software segment commands the lion’s share of the market, driven by the continuous innovation and deployment of advanced surveill

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This dataset is now a small part of Insider Trading S&P500 - Inside Info

It is important to keep an eye on large wallets when analyzing and predicting stocks

This file contains big wallet operations like Selling, Buying or Optional actions since 2021-11-10

Dataset updated to include transactions on July 27, 2022

Content

Insider Trading - A person who did the transaction Relationship - His status in the company Date - Date when the transaction was completed Transaction - A type of transaction Cost - A cost of stock in this transaction Shares - How many stocks are in the transaction Value ($) - Total value of the transaction Shares Total - Total shares of the person by this moment SEC Form 4 - Date when the transaction was recorded

Communications Surveillance for Traders Market Outlook

According to our latest research, the global Communications Surveillance for Traders market size reached USD 1.85 billion in 2024, demonstrating robust momentum driven by regulatory imperatives and technological advancements. The market is projected to grow at a CAGR of 16.8% from 2025 to 2033, reaching an estimated USD 8.12 billion by 2033. This impressive trajectory is fueled by the increasing need for proactive compliance, risk mitigation, and the adoption of sophisticated surveillance solutions across financial trading environments.

The primary growth driver for the Communications Surveillance for Traders market is the intensifying regulatory scrutiny in global financial markets. Regulatory bodies such as the SEC, FCA, and ESMA have heightened their focus on monitoring trader communications to detect insider trading, market manipulation, and other forms of misconduct. This has compelled financial institutions to invest heavily in advanced surveillance technologies that can capture, analyze, and store all forms of communication, including voice, email, instant messaging, and social media. The need to comply with stringent mandates like MiFID II and Dodd-Frank has made communications surveillance not just a compliance checkbox but a core operational requirement for trading organizations. As a result, demand for comprehensive surveillance platforms that offer real-time monitoring, automated alerts, and robust audit trails is surging worldwide.

Another significant factor propelling market expansion is the rapid evolution of communication channels and the increasing volume and complexity of data generated by traders. With the proliferation of digital messaging platforms, mobile applications, and remote trading setups, the risk landscape has expanded, making traditional surveillance tools inadequate. Modern communications surveillance solutions leverage artificial intelligence, machine learning, and natural language processing to sift through massive volumes of structured and unstructured data, flagging suspicious behaviors and patterns with greater accuracy. This technological shift is enabling financial institutions to stay ahead of sophisticated threats, maintain data integrity, and ensure operational resilience. The integration of cloud-based solutions is further enhancing scalability, flexibility, and cost-effectiveness, making advanced surveillance accessible to organizations of all sizes.

Furthermore, the growing demand for holistic risk management and fraud detection capabilities is shaping the trajectory of the Communications Surveillance for Traders market. Financial institutions are increasingly seeking unified platforms that not only address compliance requirements but also deliver actionable insights for risk mitigation and fraud prevention. The convergence of communications surveillance with broader trade surveillance, analytics, and case management functionalities is fostering the emergence of end-to-end solutions that streamline investigative workflows and support proactive decision-making. Vendors are responding by offering modular, interoperable systems that can adapt to evolving regulatory landscapes and organizational needs, thereby driving sustained market growth.

From a regional perspective, North America remains the largest market for communications surveillance solutions, underpinned by the presence of major financial hubs, early technology adoption, and a stringent regulatory environment. Europe follows closely, driven by comprehensive regulatory frameworks and a mature trading ecosystem. The Asia Pacific region, while still emerging, is exhibiting the fastest growth, fueled by expanding capital markets, increasing cross-border trading, and rising awareness of compliance best practices. Latin America and the Middle East & Africa are also witnessing gradual uptake, supported by ongoing digital transformation in their financial sectors. The interplay of global regulations, technological innovation, and regional market dynamics will continue to shape the competitive landscape and growth prospects of the market through 2033.

Component Analysis

The Communications Surveillance for Traders market by component is segmented into software, hardware, and services, each playing a pivotal role in the overall ecosystem. Software remains the largest and fastest-growing segment, accounting for over 60% of the market share in 2024. This dominance is attributed