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"source": [
"# Insider Trading Analysis with Python\n",
"\n",
"In this tutorial, we will explore how to use Python to scrape insider trading data from SEC Form 4 filings, and how to analyze the data.\n",
"\n",
"We’ll start by talking about what Form 4 filings and insiders are, then move on to discussing how you can use Python to gather the data from SEC EDGAR filings. After that, we will use various Python libraries to perform some basic analysis on the gathered data to generate potential buy and sell indicators to copy and follow insider trading activity.\n",
"\n",
"Our objective is to discover trading patterns that forecast stock price shifts. Two such examples are included as a preview below.\n",
"\n",
"The time Elon Musk sold the first batch of his Tesla shares perfectly coincided with the peak of Tesla's share price in late 2021. Subsequent sales were also reasonably well timed.\n",
"\n",
"![img](https://i.imgur.com/iXz5zen.png)\n",
"\n",
"\n",
"Buffet's Berkshire Hathaway purchased OXY shares totaling $9 billion in 2022 while perfectly timing the bottom of each retracement.\n",
"\n",
"![img2](https://i.imgur.com/tSX8DlC.png)\n",
"\n",
"\n",
"Here is an another analysis that looks at share sales made in various sectors over different years, foreshadowing the tech sell-off in 2022 with the largest insider sales in tech in 2021 for last 10 years.\n",
"\n",
"![img4](https://i.imgur.com/ffOmD8g.png)\n",
"\n",
"<!-- ![img3](https://i.imgur.com/PjtglWX.png) -->\n"
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"# Overview\n",
"\n",
"We begin by constructing our local database of insider trades for the years 2012 to 2022. To do this, we utilize the [Insider Trading Data API from SEC-API.io](https://sec-api.io/docs/insider-ownership-trading-api). The process involves: \n",
"\n",
"1. Downloading Form 3, 4 and 5 filings which have been converted from XML to JSON\n",
"2. Extracting all insider transactions from the JSON filings\n",
"3. Cleaning transactions (e.g. removing incorrectly reported trades)\n",
"4. Augmenting transactions with sector and industry information\n",
"5. Analyzing the data\n",
"\n",
"To ensure that we are on the same page, let's first define some terms before we move forward with our project.\n",
"\n",
"---\n",
"\n",
"# Basics & Definitions\n",
"\n",
"## What is insider trading?\n",
"\n",
"Insiders are famously known from movies such as Wall Street with Gordon Gekko jailed after making fortunes by trading on non-public information (aka insider information). Those types of insiders are not subject of this tutorial. We focus on the legal part of insider trading. \n",
"\n",
"The law defines the line between legal and illegal insider trading reasonably well. The reason I say \"reasonably\" is because there are still lots of holes in the rule framework that insiders use frequently to impeccably time the market (more on this later).\n",
"\n",
"In order to understand the difference between legal and illegal trading, we start with Section 16 of the Securities Exchange Act (SEA). Section 16 is a regulation that requires insiders to publicly disclose the trades in their companys' securities (stocks, options, etc.). Section 16 was first introduced in early 2000 and has been updated numerous times since. [The most recent change to Section 16 was published on December 29, 2022](https://www.govinfo.gov/content/pkg/FR-2022-12-29/pdf/2022-27675.pdf#page=69).\n",
"\n",
"[Insiders are defined in Section 16a-2](https://www.ecfr.gov/current/title-17/chapter-II/part-240/subject-group-ECFR4594b28bbb3a5d5/section-240.16a-2) as follows:\n",
"\n",
"> Any person and immediate family of such person who owns more than 10% of a company's securities ([includes trusts](https://www.ecfr.gov/current/title-17/chapter-II/part-240/subject-group-ECFR4594b28bbb3a5d5/section-240.16a-8#p-240.16a-8(a))), any director or officer of the issuer of such securities, and any member of an advisory board.\n",
"\n",
"\"Officer\" means an issuer's president, financial officer, accounting officer, vice-president in charge of a principal business unit (such as sales, administration or finance), and any other officer who performs a policy-making function. Examples are CEO, CFO, COO, VP of sales, and chairman of the board.\n",
"\n",
"An issuer is simply the company that issued the security. For example, Tesla is the issuer of TSLA stock.\n",
"\n",
"All definitions of the terms and more details about related SEC filings can be found in [Part 240, General Rules and Regulations of the SEA](https://www.ecfr.gov/current/title-17/chapter-II/part-240).\n",
"\n",
"> There are three other types of SEC filings disclosing trades in a public company, that is Form 13D, 13G and 13F. See details at the end of the tutorial. Such filings are not topic of the analysis.\n",
"\n",
"In summary, Section 16 defines the disclosure framework of insider trades such as when and how many securities were purchased/sold, what types of securities were purchased/sold and who performed the transaction.\n",
"\n",
"## Swing-Trading by Insiders \n",
"\n",
"[Section 16b](https://www.ecfr.gov/current/title-17/chapter-II/part-240/subject-group-ECFRc96807fa2565b1d#p-240.16b-6(c)) prevents insiders from performing profitable short-term swing trades and is also called the \"short-swing profit rule\". The regulation requires insiders to return to the company any profits made from the purchase/sale of company stock if both transactions occur within a six-month period.\n",
"\n",
"## What is an insider trade?\n",
"\n",
"It's simply a buy or sell order in the company's securities performed by an insider. It could be a sales of the company's stock, exercising options, or receiving additional stocks as part of a bonus payout.\n",
"\n",
"## How is an insider trade reported?\n",
"\n",
"Insider trades are disclosed on three different forms.\n",
"\n",
"- Form 3 discloses the ownership after an IPO or other security registration events. It's only filed after the registration.\n",
"- Form 4 discloses the change of ownership and is filed every time a change (buy/sell) occurred. \n",
"- Form 5 is an annual statement of ownership structure.\n",
"\n",
"[Form 3, 4 and 5](https://www.ecfr.gov/current/title-17/chapter-II/part-240/subject-group-ECFR4594b28bbb3a5d5/section-240.16a-3) are published on the SEC EDGAR system as a HTML and XML document. For this tutorial, we use all three form types and the XML-to-JSON converted data of each filing type.\n",
"\n",
"## When does an insider trade have to be reported with the SEC?\n",
"\n",
"- [Form 3](https://www.ecfr.gov/current/title-17/chapter-II/part-240/subject-group-ECFR4594b28bbb3a5d5/section-240.16a-3#p-240.16a-3(a)) is filed during the period securities are initially registered, e.g. an IPO.\n",
"- [Form 4](https://www.ecfr.gov/current/title-17/chapter-II/part-240/subject-group-ECFR4594b28bbb3a5d5/section-240.16a-3#p-240.16a-3(g)(1)) is filed before the end of the second business day following the day on which the transaction has been executed.\n",
"- [Form 5](https://www.ecfr.gov/current/title-17/chapter-II/part-240/subject-group-ECFR4594b28bbb3a5d5/section-240.16a-3#p-240.16a-3(f)(1)) is filed within 45 days after the issuer's fiscal year end, and discloses the holdings and transactions not reported previously on Forms 3, 4 or 5.\n",
"\n",
"\n",
"## What is included in Form 4 and how is it structured?\n",
"\n",
"Form 4 content always follows a standardized structure and includes:\n",
"- Information about the company: company name, ticker, CIK\n",
"- Information about the insider: name, position, relationship to the company (director, 10% owner, etc.)\n",
"- Transaction details:\n",
"\t- Were securities acquired/disposed?\n",
" - What type of securities were acquired/disposed (stocks, options, notes, warrants, etc.)?\n",
"\t- How many securities acquired/disposed and at what price?\n",
"\t- How many securities does the insider own after the transaction?\n",
"- Footnotes with full-text details about the transactions. For example, indicating that transactions fall under Rule 10b5-1.\n",
"\n",
"The below figure depicts a Form 4 filing for one of Elon Musk's Tesla share sales in July 2022 ([source file on EDGAR](https://www.sec.gov/Archives/edgar/data/1318605/000089924322035393/xslF345X03/doc4.xml)). \n",
"\n",
"The yellow marked areas represent the most important details in Form 4 filings, that being the \n",
"- reporting person (Musk), \n",
"- issuer (Tesla), \n",
"- transaction details (buy vs sell, amount of shares acquired/disposed and the price) \n",
"- and footnotes. \n",
"\n",
"The owner of the security (Elon Musk) is called the **reporter**. \n",
"The company (Tesla) that issued the securities is called the **issuer**.\n",
"\n",
"Important to note is that some reporters state the total price paid for the entire transaction rather than the price per share. Elon correctly reported all his transactions on a price per share basis. However, we need to be aware of this confusion in order to adjust for such cases during the data cleaning process."
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"![img](https://i.imgur.com/blgo5iE.png)"
],
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"cell_type": "markdown",
"source": [
"## What are derivative vs. non-derivative transactions?\n",
"\n",
"The Form 4 example above showed two tables, Table I listing non-derivative transactions and Table II holding derivative transactions. A non-derivative is the financial term for things we mostly call stocks, while derivatives represent things we know as options or futures.\n",
"\n",
"![img](https://i.imgur.com/LBJNlDC.png)"
],
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"source": [
"## What is a 10b5-1 trading plan?\n",
"\n",
"[Section 10b5-1](https://www.ecfr.gov/current/title-17/chapter-II/part-240/subpart-A/subject-group-ECFR71e2d22647918b0/section-240.10b5-1#p-240.10b5-1(b)) of the SEA makes it illegal for anyone (not only insiders) to trade on the basis of material nonpublic information. \n",
"\n",
"\"[Material](https://www.law.cornell.edu/definitions/index.php?width=840&height=800&iframe=true&def_id=c9640e72263ad5d1d09ddc21586591d9&term_occur=999&term_src=Title:17:Chapter:II:Part:240:Subpart:A:Subjgrp:68:240.10b5-1)\" just means that the information is highly likely to influence an investor's buy or sell decision. The change of a CEOs home address would be the opposite of material information.\n",
"\n",
"When we refer to \"insider information\" or \"nonpublic information\", we always mean \"material nonpublic information\", for example a merger agreement the CEO knows about but that hasn't been announced yet.\n",
"\n",
"Insiders always have access to nonpublic information, otherwise they wouldn't be classified as insiders. But insiders also like to buy and sell their stocks without performing a crime. \n",
"\n",
"So, how does the law solves this dilemma? By introducing exemptions from the rule, so called [affirmative defenses](https://www.ecfr.gov/current/title-17/chapter-II/part-240/subpart-A/subject-group-ECFR71e2d22647918b0/section-240.10b5-1#p-240.10b5-1(c)). In other words, an insider is allowed to trade his stock if he demonstrates that:\n",
"\n",
"- Before becoming aware of the information, the insider had adopted a written plan for trading securities\n",
"- The plan specifies the amount of securities to be purchased/sold and the price at which and the date on which the securities were to purchased/sold\n",
"- The insider acted in accordance to the plan\n",
"\n",
"This plan is often referred to as \"rule 10b5-1 plan\".\n",
"\n",
"In other words, an insider is allowed to buy/sell securities at predefined periods of the year, but is not allowed to perform any orders outside of this trading calendar. If that happens, the trade is classified as illegal. \n",
"\n",
"The plans are voluntarily disclosed to the public, and have to be approved by the director/s of the company. The disclosure mostly happens via 8-K filings in \"Item 8.01 Other Event\". Most companies choose not to publish them for reasons we cover later.\n",
"\n",
"The following is an example of a voluntary notification informing the public about the adoption of a 10b5-1 sales plan ([source filing](https://www.sec.gov/Archives/edgar/data/1140859/000114085922000115/abc-20221213.htm)).\n",
"\n",
"![img](https://i.imgur.com/OgqDcZA.png)\n",
"\n",
"\n",
"If an insider transaction is covered by Rule 10b5-1, is disclosed in the footnotes of each transaction. Hence, if the filing doesn't mention anything about Rule 10b5-1, it's safe to assume that the Rule doesn't apply.\n",
"\n",
"Why is this important? We try to identify whether Form 4 reported insider trades carry any predictive information about a company's future stock price. However, the law prohibits insiders from trading on material nonpublic information that might move the stock price after it has become public. So, we need to be aware that most of the transactions reported under Rule 10b5-1 might not carry any signal. Having said this, research has shown that insiders still report transactions under Rule 10b5-1 while somehow brilliantly time the market by adjusting their trading plans.\n",
"\n"
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"source": [
"## What are transaction codes?\n",
"\n",
"Each transaction reported on Form 4 is tagged with a transaction code and classifies the transaction. For example, the insider transaction in the figure below represents a sales order identifiably by the `D` (=disposed) flag with the code `S` standing for \"open market or private sale of non-derivative or derivative security\".\n",
"\n",
"![img](https://i.imgur.com/svJ5vkX.png)\n",
"\n",
"A list of all transaction codes follows.\n",
"\n",
"![img](https://i.imgur.com/mClypyt.png)\n",
"\n",
"We will see in our analysis that the most used transaction codes measured by the total dollar amount of transactions reported are `S` and `P`.\n",
"\n",
"We will see in our analysis that the most used transaction codes, measured by the total dollar amount of transactions, are `S` and `P`, where `D,S` represents an open market order to sell securities or a private sale and `A,P` an open market purchase or private purchase.\n",
"\n",
"![img](https://i.imgur.com/a4lRvc2.png)"
],
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"cell_type": "markdown",
"source": [
"# Data Gathering"
],
"metadata": {
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{
"cell_type": "markdown",
"source": [
"We begin with installing the [`sec-api`](https://pypi.org/project/sec-api/) Python package and a helper library called `pydash`. The `InsiderTradingApi` interface helps us building our local database of insider transactions while pydash helps us accessing nested JSON objects in a fail-save manner."
],
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{
"cell_type": "code",
"source": [
"pip -q install sec-api"
],
"metadata": {
"id": "Gf62AeDdQRbc"
},
"execution_count": 6,
"outputs": []
},
{
"cell_type": "code",
"source": [
"pip -q install pydash"
],
"metadata": {
"id": "y8b2_HcpQqAC"
},
"execution_count": 7,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"Head over to [SEC-API.io](https://sec-api.io/signup/free) to get your free API key and insert the key."
],
"metadata": {
"id": "6maYTn_-52rP"
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{
"cell_type": "code",
"source": [
"from sec_api import InsiderTradingApi\n",
"import pandas as pd\n",
"import math\n",
"from pydash import get, flatten\n",
"import json\n",
"\n",
"insiderTradingApi = InsiderTradingApi(\"YOUR_API_KEY\")"
],
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"id": "ApQOQq23Qrpr"
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"execution_count": 8,
"outputs": []
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"cell_type": "markdown",
"source": [
"Let's take the API for a test-spin. The `get_data()` method provides a search interface that accepts a JSON formatted search query and returns all Form 3, 4 and 5 filings that match our query. The return value represents a JSON object (Python dictionary) that holds matching filings in a list behind the `transactions` key. \n",
"\n",
"### Search Query\n",
"\n",
"A search query object has the following keys:\n",
"- `query.queryString.query` (string) defines our search criteria and is written in Lucene syntax. [More information on the Lucene syntax is available here](https://www.lucenetutorial.com/lucene-query-syntax.html). For example, the query string `issuer.tradingSymbol:TSLA` returns all insider trades in Tesla's stock. If we want to look at a specific date range, we use the range operator like this `filedAt:[2022-01-01 TO 2022-01-31]`.\n",
"- `from` (string) defines the starting position of our search, e.g. `0`. It is the same as the `OFFSET` property in an SQL statement or an index position of an array. `from` cannot exceed 10,000. \n",
"- `size` (string) defines the number of disclosures/forms that should be returned per API call (default: 50, max: 50). The insider trading database holds millions of disclosures and downloading the entire database with one API call is just not feasible. Hence, we need to paginate through our search universe by increasing the `from` parameter.\n",
"- `sort` (list) defines the sorting order of the returned disclosures. For example, `[{ \"filedAt\": { \"order\": \"desc\" } }]` returns filings descendingly sorted by their `filedAt` property (newst filing first).\n",
"\n",
"### Response\n",
"\n",
"Every item in the `transactions` list represents a single insider trading disclosure (Form 3/4/5) including all buy/sell transactions and meta data (details about reporting person, company, etc.) and is formatted as a Python dictionary.\n",
"\n",
"[The complete structure of the response is described in the official documentation here.](https://sec-api.io/docs/insider-ownership-trading-api#response-format)"
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"cell_type": "code",
"source": [
"# get the two most recently filed TSLA's insider trades\n",
"query_string = \"issuer.tradingSymbol:TSLA\"\n",
"insider_trades_sample = insiderTradingApi.get_data({\n",
" \"query\": {\"query_string\": {\"query\": query_string}},\n",
" \"from\": \"0\",\n",
" \"size\": \"2\",\n",
" \"sort\": [{ \"filedAt\": { \"order\": \"desc\" } }]\n",
"})"
],
"metadata": {
"id": "EwoiNd4MQvWj"
},
"execution_count": 9,
"outputs": []
},
{
"cell_type": "code",
"source": [
"print(json.dumps(insider_trades_sample,indent=2))"
],
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"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "GCsAMRV_67HS",
"outputId": "c3255378-e3d0-449d-c825-772ba963b3d2"
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"execution_count": 10,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"{\n",
" \"total\": {\n",
" \"value\": 710,\n",
" \"relation\": \"eq\"\n",
" },\n",
" \"transactions\": [\n",
" {\n",
" \"id\": \"26ae4efe3f5b271d5f2c2d7d0cab9032\",\n",
" \"accessionNo\": \"0001771364-23-000002\",\n",
" \"filedAt\": \"2023-01-06T21:33:29-05:00\",\n",
" \"schemaVersion\": \"X0306\",\n",
" \"documentType\": \"4\",\n",
" \"periodOfReport\": \"2023-01-04\",\n",
" \"notSubjectToSection16\": false,\n",
" \"issuer\": {\n",
" \"cik\": \"1318605\",\n",
" \"name\": \"Tesla, Inc.\",\n",
" \"tradingSymbol\": \"TSLA\"\n",
" },\n",
" \"reportingOwner\": {\n",
" \"cik\": \"1771364\",\n",
" \"name\": \"Kirkhorn Zachary\",\n",
" \"address\": {\n",
" \"street1\": \"C/O TESLA, INC.\",\n",
" \"street2\": \"1 TESLA ROAD\",\n",
" \"city\": \"AUSTIN\",\n",
" \"state\": \"TX\",\n",
" \"zipCode\": \"78725\"\n",
" },\n",
" \"relationship\": {\n",
" \"isDirector\": false,\n",
" \"isOfficer\": true,\n",
" \"officerTitle\": \"Chief Financial Officer\",\n",
" \"isTenPercentOwner\": false,\n",
" \"isOther\": false\n",
" }\n",
" },\n",
" \"nonDerivativeTable\": {\n",
" \"transactions\": [\n",
" {\n",
" \"securityTitle\": \"Common Stock\",\n",
" \"transactionDate\": \"2023-01-04\",\n",
" \"coding\": {\n",
" \"formType\": \"4\",\n",
" \"code\": \"S\",\n",
" \"equitySwapInvolved\": false,\n",
" \"footnoteId\": [\n",
" \"F1\"\n",
" ]\n",
" },\n",
" \"amounts\": {\n",
" \"shares\": 3752.25,\n",
" \"pricePerShare\": 109.31,\n",
" \"pricePerShareFootnoteId\": [\n",
" \"F2\"\n",
" ],\n",
" \"acquiredDisposedCode\": \"D\"\n",
" },\n",
" \"postTransactionAmounts\": {\n",
" \"sharesOwnedFollowingTransaction\": 200411.25\n",
" },\n",
" \"ownershipNature\": {\n",
" \"directOrIndirectOwnership\": \"D\"\n",
" }\n",
" }\n",
" ]\n",
" },\n",
" \"footnotes\": [\n",
" {\n",
" \"id\": \"F1\",\n",
" \"text\": \"The sales reported on this Form 4 were effected pursuant to a Rule 10b5-1 trading plan adopted by the reporting person on July 29, 2022.\"\n",
" },\n",
" {\n",
" \"id\": \"F2\",\n",
" \"text\": \"The price reported in Column 4 is a weighted average price. These shares were sold in multiple transactions at prices ranging from $109.090 to $109.310, inclusive. The reporting person undertakes to provide Tesla, Inc., any security holder of Tesla, Inc. or the staff of the Securities and Exchange Commission, upon request, full information regarding the number of shares sold at each separate price within the range set forth in this footnote.\"\n",
" }\n",
" ],\n",
" \"ownerSignatureName\": \"By: Aaron Beckman, Power of Attorney For: Zachary J. Kirkhorn\",\n",
" \"ownerSignatureNameDate\": \"2023-01-06\"\n",
" },\n",
" {\n",
" \"id\": \"749cd44aa5c0a2fd4705cc798b8c7104\",\n",
" \"accessionNo\": \"0001771364-23-000001\",\n",
" \"filedAt\": \"2023-01-03T21:04:57-05:00\",\n",
" \"schemaVersion\": \"X0306\",\n",
" \"documentType\": \"4/A\",\n",
" \"periodOfReport\": \"2022-12-28\",\n",
" \"dateOfOriginalSubmission\": \"2022-12-30\",\n",
" \"notSubjectToSection16\": false,\n",
" \"issuer\": {\n",
" \"cik\": \"1318605\",\n",
" \"name\": \"Tesla, Inc.\",\n",
" \"tradingSymbol\": \"TSLA\"\n",
" },\n",
" \"reportingOwner\": {\n",
" \"cik\": \"1771364\",\n",
" \"name\": \"Kirkhorn Zachary\",\n",
" \"address\": {\n",
" \"street1\": \"C/O TESLA, INC.\",\n",
" \"street2\": \"1 TESLA ROAD\",\n",
" \"city\": \"AUSTIN\",\n",
" \"state\": \"TX\",\n",
" \"zipCode\": \"78725\"\n",
" },\n",
" \"relationship\": {\n",
" \"isDirector\": false,\n",
" \"isOfficer\": true,\n",
" \"officerTitle\": \"Chief Financial Officer\",\n",
" \"isTenPercentOwner\": false,\n",
" \"isOther\": false\n",
" }\n",
" },\n",
" \"nonDerivativeTable\": {\n",
" \"transactions\": [\n",
" {\n",
" \"securityTitle\": \"Common Stock\",\n",
" \"transactionDate\": \"2022-12-28\",\n",
" \"coding\": {\n",
" \"formType\": \"4\",\n",
" \"code\": \"M\",\n",
" \"equitySwapInvolved\": false\n",
" },\n",
" \"amounts\": {\n",
" \"shares\": 13350,\n",
" \"sharesFootnoteId\": [\n",
" \"F1\"\n",
" ],\n",
" \"pricePerShare\": 18.44,\n",
" \"acquiredDisposedCode\": \"A\"\n",
" },\n",
" \"postTransactionAmounts\": {\n",
" \"sharesOwnedFollowingTransaction\": 204163.5,\n",
" \"sharesOwnedFollowingTransactionFootnoteId\": [\n",
" \"F1\"\n",
" ]\n",
" },\n",
" \"ownershipNature\": {\n",
" \"directOrIndirectOwnership\": \"D\"\n",
" }\n",
" }\n",
" ]\n",
" },\n",
" \"derivativeTable\": {\n",
" \"transactions\": [\n",
" {\n",
" \"securityTitle\": \"Incentive Stock Option (right to buy)\",\n",
" \"conversionOrExercisePrice\": 18.44,\n",
" \"transactionDate\": \"2022-12-28\",\n",
" \"coding\": {\n",
" \"formType\": \"4\",\n",
" \"code\": \"M\",\n",
" \"equitySwapInvolved\": false\n",
" },\n",
" \"exerciseDateFootnoteId\": [\n",
" \"F2\"\n",
" ],\n",
" \"expirationDate\": \"2028-10-16\",\n",
" \"underlyingSecurity\": {\n",
" \"title\": \"Common Stock\",\n",
" \"shares\": 13350,\n",
" \"sharesFootnoteId\": [\n",
" \"F1\"\n",
" ]\n",
" },\n",
" \"amounts\": {\n",
" \"shares\": 13350,\n",
" \"sharesFootnoteId\": [\n",
" \"F1\"\n",
" ],\n",
" \"pricePerShare\": 0,\n",
" \"acquiredDisposedCode\": \"D\"\n",
" },\n",
" \"postTransactionAmounts\": {\n",
" \"sharesOwnedFollowingTransaction\": 5415,\n",
" \"sharesOwnedFollowingTransactionFootnoteId\": [\n",
" \"F1\"\n",
" ]\n",
" },\n",
" \"ownershipNature\": {\n",
" \"directOrIndirectOwnership\": \"D\"\n",
" }\n",
" }\n",
" ]\n",
" },\n",
" \"footnotes\": [\n",
" {\n",
" \"id\": \"F1\",\n",
" \"text\": \"This Form 4 is being amended to correct the reported option exercise amount and holdings of the Reporting Person as of December 28, 2022, following the exercise of 13,350 options on December 28, 2022.\"\n",
" },\n",
" {\n",
" \"id\": \"F2\",\n",
" \"text\": \"1/60th of the shares subject to the option became vested and exercisable on November 1, 2018, and 1/60th of the shares subject to the option shall become vested and exercisable each month thereafter, so that all such shares subject to this option shall be fully vested as of October 1, 2023.\"\n",
" }\n",
" ],\n",
" \"ownerSignatureName\": \"By: Aaron Beckman, Power of Attorney For: Zachary J. Kirkhorn\",\n",
" \"ownerSignatureNameDate\": \"2023-01-03\"\n",
" }\n",
" ]\n",
"}\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"Having inspected two examples of insider trading disclosures, we need to find a way to structure the response data and convert it into a pandas dataframe. That's the job of the following `flatten_filing()` function.\n",
"\n",
"The function `flatten_filing()` takes as an argument a JSON formatted filing from the SEC EDGAR system that contains insider trading information. The function extracts data points from the filing such as all derivative and non-derivative transactions, the period of report (=date of transaction), issuer CIK, issuer ticker, reporting person's name, reporting person's CIK, and their relationship. It then creates a list called `transactions`, which will contain all the extracted insider trades. The code then checks if the filing contains either derivative or non-derivative transactions. If it does, the code extracts data points such as the \n",
"- type of transaction (bought or sold), \n",
"- security title (common stock, warrant, etc.), \n",
"- transaction code, \n",
"- number of shares acquired/disposed, \n",
"- share price, \n",
"- total $ amount of transaction, and \n",
"- shares owned following the transaction.\n",
"\n",
"The `total` $ amount of the transaction is calculated by simply multiplying the number of shares with the price per transaction. It then merges the extracted data points with the `base_data` and appends them to the `transactions` list. Finally, the function returns the `transactions` list."
],
"metadata": {
"id": "uvykaCObBP0Q"
}
},
{
"cell_type": "code",
"source": [
"def flatten_filing(filing):\n",
" transactions = []\n",
"\n",
" # data points to be added to each transaction\n",
" try:\n",
" base_data = {\n",
" \"periodOfReport\": filing[\"periodOfReport\"], \n",
" \"issuerCik\": filing[\"issuer\"][\"cik\"],\n",
" \"issuerTicker\": filing[\"issuer\"][\"tradingSymbol\"],\n",
" \"reportingPersonName\": get(filing, \"reportingOwner.name\", \"\"),\n",
" \"reportingPersonCik\": get(filing, \"reportingOwner.cik\", \"\"),\n",
" \"relationship\": get(filing, \"reportingOwner.relationship\", {})\n",
" }\n",
" except Exception as e:\n",
" print(f'{filing[\"id\"]}, caught {type(e)}: {e}')\n",
" return transactions\n",
"\n",
" if \"derivativeTable\" in filing and \"transactions\" in filing[\"derivativeTable\"]:\n",
" # extract the data points of interest from each transaction\n",
" for transaction in filing[\"derivativeTable\"][\"transactions\"]:\n",
" shares = get(transaction, \"amounts.shares\", 0)\n",
" sharePrice = get(transaction, \"amounts.pricePerShare\", 0)\n",
" sharesOwnedFollowingTransaction = get(transaction, \"postTransactionAmounts.sharesOwnedFollowingTransaction\", 0)\n",
" codingCode = get(transaction, \"coding.code\", \"\")\n",
" underlyingSecurity = get(transaction, \"underlyingSecurity.title\", \"\")\n",
"\n",
" entry = {\n",
" \"type\": \"derivative\",\n",
" \"securityTitle\": transaction[\"securityTitle\"],\n",
" \"underlyingSecurity\": underlyingSecurity,\n",
" \"codingCode\": codingCode,\n",
" \"acquiredDisposed\": transaction[\"amounts\"][\"acquiredDisposedCode\"],\n",
" \"shares\": shares,\n",
" \"sharePrice\": sharePrice,\n",
" \"total\": math.ceil(shares * sharePrice),\n",
" \"sharesOwnedFollowingTransaction\": sharesOwnedFollowingTransaction\n",
" }\n",
"\n",
" # merge base_data and entry into a new dict and append to transactions\n",
" transactions.append({**base_data, **entry})\n",
"\n",
" if \"nonDerivativeTable\" in filing and \"transactions\" in filing[\"nonDerivativeTable\"]:\n",
" # extract the data points of interest from each transaction\n",
" for transaction in filing[\"nonDerivativeTable\"][\"transactions\"]:\n",
" sharePrice = get(transaction, \"amounts.pricePerShare\", 0)\n",
" sharesOwnedFollowingTransaction = get(transaction, \"postTransactionAmounts.sharesOwnedFollowingTransaction\", 0)\n",
"\n",
" entry = {\n",
" \"type\": \"nonDerivative\",\n",
" \"securityTitle\": transaction[\"securityTitle\"],\n",
" \"codingCode\": transaction[\"coding\"][\"code\"],\n",
" \"acquiredDisposed\": transaction[\"amounts\"][\"acquiredDisposedCode\"],\n",
" \"shares\": transaction[\"amounts\"][\"shares\"],\n",
" \"sharePrice\": sharePrice,\n",
" \"total\": math.ceil(transaction[\"amounts\"][\"shares\"] * sharePrice),\n",
" \"sharesOwnedFollowingTransaction\": sharesOwnedFollowingTransaction\n",
" }\n",
"\n",
" # merge base_data and entry into a new dict and append to transactions\n",
" transactions.append({**base_data, **entry})\n",
"\n",
" return transactions\n",
"\n",
"\n",
"# convert `filings` into a pandas dataframe\n",
"def flatten_filings(filings):\n",
" unflattened_list = list(map(flatten_filing, filings))\n",
" return [item for sublist in unflattened_list for item in sublist]"
],
"metadata": {
"id": "Dfj-A0C-Q077"
},
"execution_count": 11,
"outputs": []
},
{
"cell_type": "code",
"source": [
"transactions = flatten_filings(insider_trades_sample[\"transactions\"])\n",
"trades = pd.DataFrame(transactions)\n",
"trades.head(5)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 364
},
"id": "tczTrT9OQ7t6",
"outputId": "2843e8d7-d02a-4693-dd57-a03e43c33a34"
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"execution_count": 12,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" periodOfReport issuerCik issuerTicker reportingPersonName \\\n",
"0 2023-01-04 1318605 TSLA Kirkhorn Zachary \n",
"1 2022-12-28 1318605 TSLA Kirkhorn Zachary \n",
"2 2022-12-28 1318605 TSLA Kirkhorn Zachary \n",
"\n",
" reportingPersonCik relationship \\\n",
"0 1771364 {'isDirector': False, 'isOfficer': True, 'offi... \n",
"1 1771364 {'isDirector': False, 'isOfficer': True, 'offi... \n",
"2 1771364 {'isDirector': False, 'isOfficer': True, 'offi... \n",
"\n",
" type securityTitle codingCode \\\n",
"0 nonDerivative Common Stock S \n",
"1 derivative Incentive Stock Option (right to buy) M \n",
"2 nonDerivative Common Stock M \n",
"\n",
" acquiredDisposed shares sharePrice total \\\n",
"0 D 3752.25 109.31 410159 \n",
"1 D 13350.00 0.00 0 \n",
"2 A 13350.00 18.44 246175 \n",
"\n",
" sharesOwnedFollowingTransaction underlyingSecurity \n",
"0 200411.25 NaN \n",
"1 5415.00 Common Stock \n",
"2 204163.50 NaN "
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},
"metadata": {},
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]
},
{
"cell_type": "markdown",
"source": [
"Excellent, our first test run was a success. Let's continue with building the code that downloads all disclosures for last 10 years.\n",
"\n",
"We use a simple JSON-NL (new line) formatted text file to store all insider transactions. This format makes it easier to start, stop and continue downloading transactions as the data parser doesn't need to load the entire text file, but rather processes each line at a time. JSON-NL allows us to read/write a single JSON object per line where each line is simply terminated with the `\\n` character.\n",
"\n",
"One year worth of filtered insider trading data is around 100MB. So, eleven years (2012 to 2022) is about 1GB of data, with derivative transactions removed.\n",
"\n",
"The function `download_and_save_trades_per_year()` downloads and saves all insider trades for a specified year in a log file named \"trades\\_[year].txt\". It takes a parameter of `year` which defaults to `2022` and opens or creates the log file in append mode. The function then enters a while loop that fetches new insider disclosures with the `get_data()` method to get data from the specified day in batches of 50 transactions at a time. If there are no more transactions for that day, it increments the day by one and checks if it is equal to the end of the year. If so it breaks out of the loop and closes the output file; otherwise, it continues on with getting new data for that day. \n",
"\n",
"The `flatten_filings()` function is then used to transform the transactions into a simpler format before they are written out to the log file as JSON strings using `json.dumps()`. A progress indicator is also printed out every 500 filings saved so you can track how many have been retrieved thus far. Finally after all trades have been downloaded for that year, a summary line is printed indicating how many total filings were saved for the given year before exiting out of the function.\n",
"\n",
"The fastest way to download all filings is by running your Python application on an AWS EC2 instance hosted in the AWS US-East-1 region."
],
"metadata": {
"id": "rMo4kYRnRnZJ"
}
},
{
"cell_type": "code",
"source": [
"from datetime import datetime, timedelta\n",
"\n",
"def download_and_save_trades_per_year(year=\"2022\"):\n",
" log_file = open(f\"trades_{year}.txt\", \"a\") \n",
"\n",
" has_data = True\n",
" start_from = 0\n",
" total_filings_saved = 0\n",
" last_count = 0\n",
" date_format = \"%Y-%m-%d\"\n",
" day = year + \"-01-01\"\n",
"\n",
" while has_data:\n",
" insider_trades = insiderTradingApi.get_data({\n",
" \"query\": {\"query_string\": {\"query\": f\"periodOfReport:{day} AND issuer.tradingSymbol:*\"}},\n",
" \"from\": start_from,\n",
" \"size\": \"50\",\n",
" \"sort\": [{ \"filedAt\": { \"order\": \"desc\" } }]\n",
" })\n",
"\n",
" if len(insider_trades[\"transactions\"]) == 0:\n",
" start_from = 0\n",
" day_date = datetime.strptime(day, date_format) + timedelta(days=1)\n",
" day = day_date.strftime(date_format)\n",
" print(f'-- {day} --')\n",
"\n",
" if day == year + \"-12-31\":\n",
" break \n",
"\n",
" continue\n",
"\n",
" total_filings_saved += len(insider_trades[\"transactions\"])\n",
" start_from += 50\n",
" \n",
" trades = flatten_filings(insider_trades[\"transactions\"])\n",
"\n",
" for trade in trades:\n",
" log_file.write(json.dumps(trade) + '\\n')\n",
"\n",
" if total_filings_saved > last_count + 500:\n",
" last_count = total_filings_saved\n",
" print(f'{total_filings_saved } saved')\n",
"\n",
" log_file.close()\n",
" print(f'{year} done. {total_filings_saved} total filings saved')\n",
"\n",
"# uncomment line below if you want to download all transactions for 2022\n",
"# download_and_save_trades_per_year(year=\"2022\")"
],
"metadata": {
"id": "hW2TSbaGR2CF"
},
"execution_count": 13,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"# Loading all Insider Trades into a Dataframe\n",
"\n",
"I downloaded all transactions and uploaded every \"trades\\_[year].txt\" file to one of my Google Drive folders. Next, we just mount my/your Google Drive and allow Goolge Colab to read the files from Drive. This way we don't have to upload all transaction files into Google Colab every time it restarts. A \"Allow Access\" window pops up, make sure to allow Colab to access your Google Drive.\n"
],
"metadata": {
"id": "P9SzXJUmRlF5"
}
},
{
"cell_type": "code",
"source": [
"from google.colab import drive\n",
"drive.mount('/content/drive')"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "LytAMvjkRm5B",
"outputId": "dd8f5771-9eec-4f41-e453-1e98e429702b"
},
"execution_count": 14,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Mounted at /content/drive\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"The `load_trades_from_file_per_year()` function loads the trades file for a specified year from your Google Drive folder and converts the JSON-NL transaction objects into a pandas dataframe. For each transaction, it ensure all the tickers in the `issuerTicker` column are upper-cased and have no whitespace and converts the `periodOfReport` column to a datetime format.\n",
"\n",
"The `load_all_trades_from_drive()` function then simply runs `load_trades_from_file_per_year()` for every year from 2012 to 2022 and merges all transactions into one giant dataframe holding 1GB+ of insider trades."
],
"metadata": {
"id": "akvaUYfbTFWU"
}
},
{
"cell_type": "code",
"source": [
"pip -q install jsonlines"
],
"metadata": {
"id": "AAAiAn5rRiRG"
},
"execution_count": 15,
"outputs": []
},
{
"cell_type": "code",
"source": [
"import jsonlines\n",
"import datetime as dt\n",
"\n",
"def load_trades_from_file_per_year(year=\"2022\"):\n",
" trades = []\n",
"\n",
" with jsonlines.open(f\"/content/drive/MyDrive/Colab Notebooks/insider-trading-monitor/trades-{year}.txt\") as reader:\n",
" for trade in reader:\n",
" trades.append(trade)\n",
"\n",
" trades_df = pd.DataFrame(trades)\n",
"\n",
" trades_df.drop('filingId', axis=1, inplace=True)\n",
"\n",
" trades_df[\"issuerTicker\"] = trades_df[\"issuerTicker\"].apply(lambda x : x.upper().replace(\" \", \"\"))\n",
"\n",
" trades_df['periodOfReport'] = pd.to_datetime(trades_df['periodOfReport'])\n",
"\n",
" return trades_df\n",
"\n",
"\n",
"trades_2022 = load_trades_from_file_per_year(year=\"2022\")\n",
"\n",
"trades_2022.head(10)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 427
},
"id": "FxL7kLRsS3zZ",
"outputId": "85361e7a-9ef4-4392-f168-e6e7182ba9c4"
},
"execution_count": 16,
"outputs": [
{
"output_type": "execute_result",
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" periodOfReport issuerCik issuerTicker reportingPerson securityTitle \\\n",
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"\n",
" codingCode acquiredDisposed shares sharePrice total \\\n",
"0 M A 235.0 0.00 0 \n",
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"7 F D 1608.0 21.01 33785 \n",
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"9 F D 679.0 13.21 8970 \n",
"\n",
" sharesOwnedFollowingTransaction \n",
"0 235.0 \n",
"1 950.0 \n",
"2 559.0 \n",
"3 10319.0 \n",
"4 10677.0 \n",
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},
"metadata": {},
"execution_count": 16
}
]
},
{
"cell_type": "code",
"source": [
"def load_all_trades_from_drive():\n",
" all_trades = pd.DataFrame()\n",
"\n",
" for year in range(2012, 2023):\n",
" trades_per_year = load_trades_from_file_per_year(year=year)\n",
"\n",
" all_trades = pd.concat([all_trades, trades_per_year])\n",
"\n",
" return all_trades"
],
"metadata": {
"id": "o4kPOFCp1FNe"
},
"execution_count": 17,
"outputs": []
},
{
"cell_type": "code",
"source": [
"all_trades = load_all_trades_from_drive()"
],
"metadata": {
"id": "0SrQd_Wa1ISN"
},
"execution_count": 18,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"# Data Cleaning\n",
"\n",
"In the next step, we focus on cleaning the transactions. In particular, we remove transactions from our corpus that meet any of the following criteria:\n",
"\n",
"- Number of shares = share price\n",
"- Share price > $6,000 and number of shares is not 1\n",
"- Total amount per transaction is \\$0\n",
"- Transaction code is `M` representing the exercise or conversion of derivative security exempted pursuant to Rule 16b-3\n",
"- Incorrect ticker, e.g. \"NONE\", \"N/A\"\n",
"- Incorrect reporter with CIK matching 810893, 1454510, etc."
],
"metadata": {
"id": "2jmaRVzL1YZK"
}
},
{
"cell_type": "code",
"source": [
"filter_all = (all_trades[\"shares\"] != all_trades[\"sharePrice\"]) & \\\n",
" ( (all_trades[\"sharePrice\"] < 6000) | (all_trades[\"shares\"] == 1) ) & \\\n",
" (all_trades[\"total\"] > 0) & \\\n",
" (all_trades[\"codingCode\"] != \"M\") & \\\n",
" (all_trades[\"issuerTicker\"] != \"NONE\") & \\\n",
" (all_trades[\"issuerTicker\"] != \"N/A\") & \\\n",
" (all_trades[\"issuerTicker\"] != \"NA\") & \\\n",
" (~all_trades[\"issuerCik\"].str.contains(\"810893|1454510|1463208|1877939|1556801|827187\")) # insider incorrectly reported share price"
],
"metadata": {
"id": "rjz7pJi71fpt"
},
"execution_count": 19,
"outputs": []
},
{
"cell_type": "code",
"source": [
"all_trades = all_trades[filter_all]"
],
"metadata": {
"id": "ZKEw06wc1h88"
},
"execution_count": 20,
"outputs": []
},
{
"cell_type": "code",
"source": [
"all_trades[(all_trades[\"sharePrice\"] > 500)].sort_values(by=[\"sharePrice\"], ascending=False).head(100)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 765
},
"id": "mjeTwKtQ1jvW",
"outputId": "fbacda02-bc1d-487c-d905-1ad8670e8552"
},
"execution_count": 21,
"outputs": [
{
"output_type": "execute_result",
"data": {
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" periodOfReport issuerCik issuerTicker reportingPerson \\\n",
"130508 2019-05-08 1750866 WEB2537 LISA MICHELLE PARKER \n",
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"... ... ... ... ... \n",
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"222986 2022-09-29 1067983 BRK.A Abel Gregory \n",
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" <td>A</td>\n",
" <td>1.0</td>\n",
" <td>4.059506e+05</td>\n",
" <td>405951</td>\n",
" <td>30.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>222987</th>\n",
" <td>2022-09-29</td>\n",
" <td>1067983</td>\n",
" <td>BRK.A</td>\n",
" <td>Abel Gregory</td>\n",
" <td>Class A Common Stock</td>\n",
" <td>P</td>\n",
" <td>A</td>\n",
" <td>1.0</td>\n",
" <td>4.059395e+05</td>\n",
" <td>405940</td>\n",
" <td>29.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>222986</th>\n",
" <td>2022-09-29</td>\n",
" <td>1067983</td>\n",
" <td>BRK.A</td>\n",
" <td>Abel Gregory</td>\n",
" <td>Class A Common Stock</td>\n",
" <td>P</td>\n",
" <td>A</td>\n",
" <td>1.0</td>\n",
" <td>4.058770e+05</td>\n",
" <td>405877</td>\n",
" <td>28.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>222985</th>\n",
" <td>2022-09-29</td>\n",
" <td>1067983</td>\n",
" <td>BRK.A</td>\n",
" <td>Abel Gregory</td>\n",
" <td>Class A Common Stock</td>\n",
" <td>P</td>\n",
" <td>A</td>\n",
" <td>1.0</td>\n",
" <td>4.058757e+05</td>\n",
" <td>405876</td>\n",
" <td>27.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>100 rows × 11 columns</p>\n",
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{
"cell_type": "markdown",
"source": [
"Cases exist where the `sharePrice` represents the total price paid for the transaction, that being `shares` * `price per share`. In other words, the reporter confused the `sharePrice` with the total amount paid per transaction. Incorrectly reported prices seem to happen mostly with OTC stocks. In order to filter out such transactions, we add the corresponding exchange of the ticker to all transactions and then remove transactions without a valid exchange.\n",
"\n",
"[A list of all tickers traded on the NYSE and NASDAQ exchange is available through the Mapping API from SEC-API.io.](https://sec-api.io/docs/mapping-api). We use the \"List All Companies by Exchange\" endpoint.\n",
"\n",
"- GET https://api.sec-api.io/mapping/exchange/nasdaq\n",
"- GET https://api.sec-api.io/mapping/exchange/nyse\n",
"\n",
"Here is an example response for a NASDAQ query:\n",
"\n",
"```json\n",
"[\n",
" {\n",
" \"name\": \"Aaon Inc\",\n",
" \"ticker\": \"AAON\",\n",
" \"cik\": \"824142\",\n",
" \"cusip\": \"000360206\",\n",
" \"exchange\": \"NASDAQ\",\n",
" \"category\": \"Domestic Common Stock\",\n",
" \"sector\": \"Basic Materials\",\n",
" \"industry\": \"Building Products & Equipment\",\n",
" \"sic\": \"3585\",\n",
" \"sicSector\": \"Manufacturing\",\n",
" \"sicIndustry\": \"Air-Cond & Warm Air Heatg Equip & Comm & Indl Refrig Equip\",\n",
" \"id\": \"7414f59fa8ea1454fe8f18f54ee80a9e\"\n",
" },\n",
" ... more mappings\n",
"]\n",
"```\n",
"\n",
"For the purpose of this tutorial, the NYSE and NASDAQ listed companies were saved in a file, `nyse.json` and `nasdaq.json`, and uploaded to Google Drive. The `load_ticker_meta_data` function loads both mapping files, merges them, removes columns we don't need, and returns a single dataframe including all listed companies."
],
"metadata": {
"id": "p3N9AAkg12mB"
}
},
{
"cell_type": "code",
"source": [
"def load_ticker_meta_data():\n",
" nyse = pd.read_json('/content/drive/MyDrive/Colab Notebooks/insider-trading-monitor/nyse.json') \n",
" nasdaq = pd.read_json('/content/drive/MyDrive/Colab Notebooks/insider-trading-monitor/nasdaq.json')\n",
"\n",
" nyse.drop([\"cusip\",\"sic\",\"famaSector\",\"famaIndustry\",\"id\", \"currency\", \"location\"], axis=1, inplace=True)\n",
" nasdaq.drop([\"cusip\",\"sic\",\"famaSector\",\"famaIndustry\",\"id\", \"currency\", \"location\"], axis=1, inplace=True)\n",
"\n",
" nyse.rename(columns={'ticker': 'issuerTicker'}, inplace=True)\n",
" nasdaq.rename(columns={'ticker': 'issuerTicker'}, inplace=True) \n",
"\n",
" return pd.concat([nyse, nasdaq])\n",
"\n",
"ticker_meta_data = load_ticker_meta_data()\n",
"ticker_meta_data.head(5)"
],
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"base_uri": "https://localhost:8080/",
"height": 389
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"id": "vBtmmjXz12Be",
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{
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"data": {
"text/plain": [
" name issuerTicker cik exchange isDelisted \\\n",
"0 AGILENT TECHNOLOGIES INC A 1090872 NYSE False \n",
"1 ALCOA CORP AA 1675149 NYSE False \n",
"2 ALTANA AKTIENGESELLSCHAFT AAAGY 1182802 NYSE True \n",
"3 ARES ACQUISITION CORP AAC 1829432 NYSE False \n",
"4 ARCADIA FINANCIAL LTD AAC1 879674 NYSE True \n",
"\n",
" category sector \\\n",
"0 Domestic Common Stock Healthcare \n",
"1 Domestic Common Stock Basic Materials \n",
"2 ADR Common Stock Healthcare \n",
"3 Domestic Common Stock Primary Class Industrials \n",
"4 Domestic Common Stock Financial Services \n",
"\n",
" industry sicSector \\\n",
"0 Diagnostics & Research Manufacturing \n",
"1 Aluminum Manufacturing \n",
"2 Biotechnology Manufacturing \n",
"3 Shell Companies Finance Insurance And Real Estate \n",
"4 Asset Management Finance Insurance And Real Estate \n",
"\n",
" sicIndustry \n",
"0 Laboratory Analytical Instruments \n",
"1 Primary Production Of Aluminum \n",
"2 Pharmaceutical Preparations \n",
"3 Blank Checks \n",
"4 Short-Term Business Credit Institutions "
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" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>ALTANA AKTIENGESELLSCHAFT</td>\n",
" <td>AAAGY</td>\n",
" <td>1182802</td>\n",
" <td>NYSE</td>\n",
" <td>True</td>\n",
" <td>ADR Common Stock</td>\n",
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" <td>Finance Insurance And Real Estate</td>\n",
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" <th>4</th>\n",
" <td>ARCADIA FINANCIAL LTD</td>\n",
" <td>AAC1</td>\n",
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" <td>NYSE</td>\n",
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{
"cell_type": "code",
"source": [
"all_trades = all_trades.merge(ticker_meta_data, on=\"issuerTicker\", how=\"left\", suffixes=(None,None))\n",
"print(len(all_trades))\n",
"all_trades = all_trades[all_trades[\"exchange\"].notna()]\n",
"print(len(all_trades))"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "ZVHGQY5U1_hE",
"outputId": "f13b79b8-3ba1-4601-d439-c79e1ee47b72"
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"execution_count": 23,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"2083370\n",
"1845618\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"We started with 2,083,370 insider trades. After dropping all transactions without an exchange, 1,845,618 trades remained.\n",
"\n",
"---\n",
"\n"
],
"metadata": {
"id": "Lg8claTgloaH"
}
},
{
"cell_type": "markdown",
"source": [
"# Analysis\n",
"\n",
"Finally, we're ready to start analyzing the data. First, we set some basic styling props for our charts and define a `millions_formatter()` helper function to format the axis of charts. The helper transforms general numbers into a financial format, for example `20000000` becomes `$ 20 M`."
],
"metadata": {
"id": "sZmGIMFx2KkO"
}
},
{
"cell_type": "code",
"source": [
"import matplotlib\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib.dates as mdates\n",
"\n",
"plt.style.use('seaborn')\n",
"\n",
"params = {'legend.fontsize': '14',\n",
" 'font.size': '14',\n",
" 'axes.labelsize': '14',\n",
" 'axes.labelweight': 'bold',\n",
" 'axes.titlesize':'14',\n",
" 'xtick.labelsize':'14',\n",
" 'ytick.labelsize':'14'\n",
" }\n",
"\n",
"plt.rcParams.update(params)\n",
"\n",
"# Prettify y axis: 2000000 to $2M\n",
"def millions_formatter(x, pos):\n",
" return '$ {:,.0f} M'.format(x*1e-6)"
],
"metadata": {
"id": "I7opdRO3TDmJ"
},
"execution_count": 24,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"To get us warmed up, we start with plotting the total amount of all purchase and sale transactions per year from 2012 to 2022. \n",
"\n",
"The following code calculates the total number of securities acquired and disposed per day. It first creates two separate dataframes, one containing the total number of securities acquired, and another containing the total number of securities disposed. It then merges these two dataframes into one, renaming the columns to `acquired` and `disposed`. The resulting dataframe holds the total $ amount of securities acquired and disposed per day."
],
"metadata": {
"id": "ZoD5ZZbFm2Y6"
}
},
{
"cell_type": "code",
"source": [
"acquired_all = all_trades[all_trades[\"acquiredDisposed\"]==\"A\"].groupby(['periodOfReport'])['total'].sum()\n",
"disposed_all = all_trades[all_trades[\"acquiredDisposed\"]==\"D\"].groupby(['periodOfReport'])['total'].sum()\n",
"\n",
"acquired_disposed_all = pd.merge(acquired_all, disposed_all, on='periodOfReport', how='outer')\n",
"acquired_disposed_all.rename(columns={'total_x': 'acquired', 'total_y': 'disposed'}, inplace=True)\n",
"acquired_disposed_all = acquired_disposed_all.sort_values(by=[\"periodOfReport\"])\n",
"\n",
"acquired_disposed_all.head(10)"
],
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" acquired disposed\n",
"periodOfReport \n",
"2012-01-01 174543582 67079942\n",
"2012-01-02 64401 12477547\n",
"2012-01-03 71052213 3640173534\n",
"2012-01-04 6238416 68464586\n",
"2012-01-05 53758753 51533545\n",
"2012-01-06 29169261 107739926\n",
"2012-01-07 9968 1716656\n",
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" </tr>\n",
" <tr>\n",
" <th>periodOfReport</th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2012-01-01</th>\n",
" <td>174543582</td>\n",
" <td>67079942</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2012-01-02</th>\n",
" <td>64401</td>\n",
" <td>12477547</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2012-01-03</th>\n",
" <td>71052213</td>\n",
" <td>3640173534</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2012-01-04</th>\n",
" <td>6238416</td>\n",
" <td>68464586</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2012-01-05</th>\n",
" <td>53758753</td>\n",
" <td>51533545</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2012-01-06</th>\n",
" <td>29169261</td>\n",
" <td>107739926</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2012-01-07</th>\n",
" <td>9968</td>\n",
" <td>1716656</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2012-01-08</th>\n",
" <td>58302</td>\n",
" <td>1997737</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2012-01-09</th>\n",
" <td>146390721</td>\n",
" <td>253880677</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2012-01-10</th>\n",
" <td>308145618</td>\n",
" <td>163315902</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>\n",
" <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a2b75c38-c877-4169-bc5a-20cb1a2fadd6')\"\n",
" title=\"Convert this dataframe to an interactive table.\"\n",
" style=\"display:none;\">\n",
" \n",
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" </svg>\n",
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" \n",
" <style>\n",
" .colab-df-container {\n",
" display:flex;\n",
" flex-wrap:wrap;\n",
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"\n",
" .colab-df-convert {\n",
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" fill: #174EA6;\n",
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"\n",
" [theme=dark] .colab-df-convert {\n",
" background-color: #3B4455;\n",
" fill: #D2E3FC;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-convert:hover {\n",
" background-color: #434B5C;\n",
" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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"\n",
" <script>\n",
" const buttonEl =\n",
" document.querySelector('#df-a2b75c38-c877-4169-bc5a-20cb1a2fadd6 button.colab-df-convert');\n",
" buttonEl.style.display =\n",
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
"\n",
" async function convertToInteractive(key) {\n",
" const element = document.querySelector('#df-a2b75c38-c877-4169-bc5a-20cb1a2fadd6');\n",
" const dataTable =\n",
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
" [key], {});\n",
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"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
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]
},
"metadata": {},
"execution_count": 25
}
]
},
{
"cell_type": "markdown",
"source": [
"Now that we have the daily statistics, we continue with the graph plotting function `plot_annual_graph`. The function plots a graph showing the amount of assets acquired and disposed of per year. It takes in our previously generate dataframe (df) `acquired_disposed_all` as input. First, it converts the index values in df to datetime objects using `pd.to_datetime()`. Then, it uses pandas' `groupby()` function to group the acquired and disposed values by year (which is specified by frequency `'Y'`, or yearly). It then merges these two DataFrames together into one and plots them as a bar graph. The graph is given titles, labels, axes formats, etc., before finally being displayed using `plt.show()`."
],
"metadata": {
"id": "sGuVWPB1pJM8"
}
},
{
"cell_type": "code",
"source": [
"def plot_annual_graph(df):\n",
" df.index = pd.to_datetime(df.index)\n",
"\n",
" acquired_yr = df.groupby(pd.Grouper(freq='Y'))['acquired'].sum()\n",
" disposed_yr = df.groupby(pd.Grouper(freq='Y'))['disposed'].sum()\n",
"\n",
" acquired_disposed_yr = pd.merge(acquired_yr, disposed_yr, on='periodOfReport', how='outer')\n",
"\n",
" ax = acquired_disposed_yr.plot.bar(stacked=False, figsize=(15, 7), color=[\"#2196f3\", \"#ef5350\"])\n",
"\n",
" ax.grid(True)\n",
" ax.yaxis.set_major_formatter(matplotlib.ticker.FuncFormatter(millions_formatter))\n",
" ax.set_xticks(range(acquired_disposed_yr.index.size))\n",
" ax.set_xticklabels([ts.strftime('%Y') for idx, ts in enumerate(acquired_disposed_yr.index)])\n",
" ax.set_xlabel(\"Year\")\n",
" ax.set_ylabel(\"Amount $\")\n",
" ax.set_title(\"Acquired/Disposed per Year\")\n",
" ax.figure.autofmt_xdate(rotation=0, ha='center')\n",
" \n",
" plt.show()"
],
"metadata": {
"id": "5MdzhwIiThxK"
},
"execution_count": 26,
"outputs": []
},
{
"cell_type": "code",
"source": [
"plot_annual_graph(acquired_disposed_all)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 430
},
"id": "j4j2ZAJI2c3e",
"outputId": "8fdd5d4e-3562-420a-bbda-87ce34614ff7"
},
"execution_count": 27,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1080x504 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
]
},
{
"cell_type": "markdown",
"source": [
"# Distribution of Transaction Codes\n",
"\n",
"Initially, we briefly covered transaction codes. The following code generates the distribution of such transaction codes measured against the total transaction volume. "
],
"metadata": {
"id": "_Ci1LAe42xiN"
}
},
{
"cell_type": "code",
"source": [
"transaction_code = all_trades\\\n",
" .groupby([\"acquiredDisposed\", \"codingCode\"])['total'] \\\n",
" .sum() \n",
"\n",
"ax_codes = transaction_code.plot.barh(figsize=(10,8))\n",
"ax_codes.xaxis.set_major_formatter(matplotlib.ticker.FuncFormatter(millions_formatter))\n",
"ax_codes.set_xlabel(\"Amount $\")\n",
"ax_codes.set_ylabel(\"Transaction Code\")\n",
"ax_codes.set_title(\"Distribution of Transaction Codes (2012 - 2022)\")\n",
"ax_codes.figure.autofmt_xdate(rotation=0, ha='center')\n",
"\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 479
},
"id": "8_QKbDPU2d1m",
"outputId": "5dee96a2-e7bf-4895-b46e-2ff884c3aff9"
},
"execution_count": 28,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 720x576 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
]
},
{
"cell_type": "markdown",
"source": [
"# Companies most often bought/sold in 2022\n",
"\n",
"Let's determine the stocks that insider bought and sold the most in 2022.\n",
"\n",
"The next part is used to get the total amount of trades acquired by ticker in 2022. It first creates a new column called `year_22`, which is a boolean value indicating whether the period of report (i.e. the date the transaction occurred) corresponds to 2022. Then it filters the `all_trades` dataframe based on the boolean value and whether `acquiredDisposed` is `A` (indicating whether it was acquired). The filtered dataframe is then grouped by `issuerTicker`, and the `total` sum for each ticker is calculated and sorted in descending order."
],
"metadata": {
"id": "d-UjX5Ln295F"
}
},
{
"cell_type": "code",
"source": [
"year_22 = all_trades['periodOfReport'].dt.year == 2022\n",
"\n",
"acquired_by_ticker = all_trades[(all_trades[\"acquiredDisposed\"]==\"A\") & year_22] \\\n",
" .groupby([\"issuerTicker\"])['total'] \\\n",
" .sum() \\\n",
" .sort_values(ascending=False)\n",
"\n",
"acquired_by_ticker.head(5)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "IqQEdDF5205P",
"outputId": "7f6b6818-ddc6-4c04-f78e-c5c8ed6a8889"
},
"execution_count": 29,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"issuerTicker\n",
"OXY 9002217384\n",
"IEP 2179778600\n",
"NLSN 1699968222\n",
"SC 1177306362\n",
"LCID 914999991\n",
"Name: total, dtype: object"
]
},
"metadata": {},
"execution_count": 29
}
]
},
{
"cell_type": "code",
"source": [
"disposed_by_ticker = all_trades[(all_trades[\"acquiredDisposed\"]==\"D\") & year_22] \\\n",
" .groupby([\"issuerTicker\"])['total'] \\\n",
" .sum() \\\n",
" .sort_values(ascending=False)\n",
"\n",
"disposed_by_ticker.head(5)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "vXNYAdSf3Fy8",
"outputId": "1b32b3b8-1390-4e37-febe-db7269d55734"
},
"execution_count": 30,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"issuerTicker\n",
"TSLA 23121540588\n",
"ANAT 9707035011\n",
"MCFE 9309015638\n",
"MSP 8715416238\n",
"STZ 5789917688\n",
"Name: total, dtype: object"
]
},
"metadata": {},
"execution_count": 30
}
]
},
{
"cell_type": "markdown",
"source": [
"The next part creates a figure with two subplots, each with a bar plot. The first plot shows the top 15 most bought companies in 2022 and the second plot shows the top 15 most sold companies in 2022."
],
"metadata": {
"id": "9_KPWbSbWvOG"
}
},
{
"cell_type": "code",
"source": [
"fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(15, 5))\n",
"\n",
"ax_ac_ti = acquired_by_ticker.head(15).sort_values(ascending=True).plot.barh(ax=axes[0], y='issuerTicker')\n",
"ax_ac_ti.xaxis.set_major_formatter(matplotlib.ticker.FuncFormatter(millions_formatter))\n",
"ax_ac_ti.set_xlabel(\"Amount $\")\n",
"ax_ac_ti.set_ylabel(\"Ticker\")\n",
"ax_ac_ti.set_title(\"Top 15 Most Bought Companies in 2022\")\n",
"ax_ac_ti.figure.autofmt_xdate(rotation=0, ha='center')\n",
"\n",
"ax_di_ti = disposed_by_ticker.head(15).sort_values(ascending=True).plot.barh(ax=axes[1], y='issuerTicker')\n",
"ax_di_ti.xaxis.set_major_formatter(matplotlib.ticker.FuncFormatter(millions_formatter))\n",
"ax_di_ti.set_xlabel(\"Amount $\")\n",
"ax_di_ti.set_ylabel(\"Ticker\")\n",
"ax_di_ti.set_title(\"Top 15 Most Sold Companies in 2022\")\n",
"ax_di_ti.figure.autofmt_xdate(rotation=0, ha='center')\n",
"\n",
"fig.tight_layout()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 361
},
"id": "ZcTmioNlrmBj",
"outputId": "ff4678b4-96f9-42f1-d243-afc12c9064df"
},
"execution_count": 31,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1080x360 with 2 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
]
},
{
"cell_type": "markdown",
"source": [
"# Insiders that sold/bought the most in 2022\n",
"\n",
"The next part deals with finding the top 10 largest sellers and buyers in 2022. Same as before, we create two dataframes, `acquired_by_insider` and `disposed_by_insider`, grouping by `reportingPerson` and `issuerTicker` and then summarizing the `total` transaction amounts per reporter and ticker.\n"
],
"metadata": {
"id": "91b8hDuQ3eVB"
}
},
{
"cell_type": "code",
"source": [
"acquired_by_insider = all_trades[(all_trades[\"acquiredDisposed\"]==\"A\") & year_22] \\\n",
" .groupby([\"reportingPerson\", \"issuerTicker\"])['total'] \\\n",
" .sum() \\\n",
" .sort_values(ascending=False)\n",
"\n",
"acquired_by_insider.head(5)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "QSbrfnka3NlP",
"outputId": "1c2b2aaa-9dd6-4a3b-b0ad-f4dde2234bac"
},
"execution_count": 32,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"reportingPerson issuerTicker\n",
"BERKSHIRE HATHAWAY INC OXY 9001419282\n",
"ICAHN CARL C IEP 2179778600\n",
"WINDACRE PARTNERSHIP LLC NLSN 1695976202\n",
"PUBLIC INVESTMENT FUND LCID 914999991\n",
"Moskovitz Dustin A. ASAN 885320147\n",
"Name: total, dtype: object"
]
},
"metadata": {},
"execution_count": 32
}
]
},
{
"cell_type": "code",
"source": [
"disposed_by_insider = all_trades[(all_trades[\"acquiredDisposed\"]==\"D\") & year_22] \\\n",
" .groupby([\"reportingPerson\", \"issuerTicker\"])['total'] \\\n",
" .sum() \\\n",
" .sort_values(ascending=False)\n",
"\n",
"disposed_by_insider.head(5)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "ZflNPtxb3wiz",
"outputId": "a0916db8-ea64-4f9c-a5ab-07a6699f2c46"
},
"execution_count": 33,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"reportingPerson issuerTicker\n",
"Musk Elon TSLA 22934307944\n",
"Intel Americas, Inc. MCFE 4561417978\n",
"Vista Equity Partners Fund VI, L.P. MSP 4038253333\n",
"VEP Group, LLC MSP 4038253333\n",
"Walgreens Boots Alliance, Inc. ABC 3930130087\n",
"Name: total, dtype: object"
]
},
"metadata": {},
"execution_count": 33
}
]
},
{
"cell_type": "code",
"source": [
"def name_formatter(tup):\n",
" name, ticker = tup\n",
" name = name[:30] + '..' if len(name) > 30 else name\n",
" return (name, ticker)\n",
"\n",
"acquired_by_insider.index = acquired_by_insider.index.map(name_formatter)\n",
"disposed_by_insider.index = disposed_by_insider.index.map(name_formatter)\n",
"\n",
"acquired_by_insider.head(5)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "UaMaK1C7wMhY",
"outputId": "54677e3f-98d0-4b93-ae75-49979410879c"
},
"execution_count": 34,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"reportingPerson issuerTicker\n",
"BERKSHIRE HATHAWAY INC OXY 9001419282\n",
"ICAHN CARL C IEP 2179778600\n",
"WINDACRE PARTNERSHIP LLC NLSN 1695976202\n",
"PUBLIC INVESTMENT FUND LCID 914999991\n",
"Moskovitz Dustin A. ASAN 885320147\n",
"Name: total, dtype: object"
]
},
"metadata": {},
"execution_count": 34
}
]
},
{
"cell_type": "code",
"source": [
"fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(20, 5))\n",
"\n",
"ax_ac_in = acquired_by_insider.head(10).sort_values(ascending=True).plot.barh(ax=axes[0], y='reportingPerson')\n",
"ax_ac_in.xaxis.set_major_formatter(matplotlib.ticker.FuncFormatter(millions_formatter))\n",
"ax_ac_in.set_xlabel(\"Amount $\")\n",
"ax_ac_in.set_ylabel(\"Insider, Ticker\")\n",
"ax_ac_in.set_title(\"Top 10 Largest Buyers in 2022\")\n",
"ax_ac_in.figure.autofmt_xdate(rotation=0, ha='center')\n",
"\n",
"ax_di_in = disposed_by_insider.head(10).sort_values(ascending=True).plot.barh(ax=axes[1], y='reportingPerson')\n",
"ax_di_in.xaxis.set_major_formatter(matplotlib.ticker.FuncFormatter(millions_formatter))\n",
"ax_di_in.set_xlabel(\"Amount $\")\n",
"ax_di_in.set_ylabel(\"Insider, Ticker\")\n",
"ax_di_in.set_title(\"Top 10 Largest Sellers 2022\")\n",
"ax_di_in.figure.autofmt_xdate(rotation=0, ha='center')\n",
"\n",
"fig.tight_layout()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 297
},
"id": "IQCpPcDDtwhZ",
"outputId": "8e15229b-a011-4690-e302-3a868f9ccf2d"
},
"execution_count": 35,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1440x360 with 2 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
]
},
{
"cell_type": "markdown",
"source": [
"# Buffet’s timing to buy OXY shares\n",
"\n",
"In the next chapter we discuss how to overlay insider transactions onto a daily stock price chart. I used my brokers' API to generate daily price statistics for a security, save the data points to a CSV file and load the file from Google Drive into the dataframe `oxy_price`."
],
"metadata": {
"id": "8n3m3vhx4ggG"
}
},
{
"cell_type": "code",
"source": [
"oxy_price = pd.read_csv('/content/drive/MyDrive/Colab Notebooks/insider-trading-monitor/OXY.csv')\n",
"\n",
"oxy_price['date'] = pd.to_datetime(oxy_price['date'])\n",
"\n",
"oxy_price = oxy_price[(oxy_price[\"date\"]>=datetime(2018, 1, 1))]\n",
"\n",
"oxy_price = oxy_price.set_index('date')\n",
"\n",
"oxy_price[\"average\"].plot(xlabel=\"Date\", ylabel=\"Price $\", title=\"OXY Daily Price Chart\", figsize=(15,7))"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 461
},
"id": "KZ4Nne3X4NQI",
"outputId": "2ae85430-f357-4ed5-8aa3-7306e6cc749f"
},
"execution_count": 36,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7ff69b7b5af0>"
]
},
"metadata": {},
"execution_count": 36
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1080x504 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
]
},
{
"cell_type": "markdown",
"source": [
"The next part is creating a DataFrame containing the total amount of trades made by the Berkshire Hathaway on OXY securities since January 1st, 2018. The first line creates a filter for `all_trades`, specifying that it should only include trades from OXY securities acquired by “BERKSHIRE”. It then groups together these trades based on the `periodOfReport` column and sums up their total values. The index names are then changed to `date` and it is merged with the daily pricing DataFrame `oxy_price`, on date. Any `NaN` values are filled with `0`."
],
"metadata": {
"id": "wAi1PAV3XZAA"
}
},
{
"cell_type": "code",
"source": [
"oxy_filter = (all_trades[\"issuerTicker\"]==\"OXY\") & \\\n",
" (all_trades[\"acquiredDisposed\"]==\"A\") & \\\n",
" (all_trades[\"periodOfReport\"]>=datetime(2018, 1, 1)) & \\\n",
" (all_trades[\"reportingPerson\"].str.contains(\"BERKSHIRE\"))\n",
"\n",
"oxy_acquired = all_trades[oxy_filter].groupby(\"periodOfReport\")[\"total\"].sum()\n",
"\n",
"oxy_acquired.index.names = ['date']"
],
"metadata": {
"id": "92jJ0VUR4nlA"
},
"execution_count": 37,
"outputs": []
},
{
"cell_type": "code",
"source": [
"oxy_all = pd.merge(oxy_price, oxy_acquired, on='date', how='outer').fillna(0)\n",
"oxy_all.head(5)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 238
},
"id": "ZPPswuHZ4s50",
"outputId": "b39e521b-72d3-43e7-b6fe-56e465243250"
},
"execution_count": 38,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" Unnamed: 0 open high low close volume \\\n",
"date \n",
"2018-01-02 1249 63.7175 63.9931 63.2868 63.7175 24267.99 \n",
"2018-01-03 1250 63.6916 64.6907 63.6916 64.5960 31392.58 \n",
"2018-01-04 1251 64.3806 64.5874 63.1060 64.5615 24332.43 \n",
"2018-01-05 1252 64.4495 64.5701 63.9500 64.2084 28760.02 \n",
"2018-01-08 1253 64.2515 64.8027 64.0878 64.7252 28326.58 \n",
"\n",
" average barCount total \n",
"date \n",
"2018-01-02 63.656311 12481 0 \n",
"2018-01-03 64.319496 16453 0 \n",
"2018-01-04 64.414237 13160 0 \n",
"2018-01-05 64.187720 15330 0 \n",
"2018-01-08 64.594244 13440 0 "
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},
"metadata": {},
"execution_count": 38
}
]
},
{
"cell_type": "markdown",
"source": [
"The `print_chart()` function takes in two arguments: `ticker_series` and `title`. It creates a data visualization of the `ticker_series` and uses a for loop to draw markers onto the price time series, where the marker size correlates to insider transaction volume. Additionally, it draws an arrow pointer at the largest insider transaction. Finally, it prints the total $ amount of securities purchased at the middle of the graph."
],
"metadata": {
"id": "klj68n-WXq3i"
}
},
{
"cell_type": "code",
"source": [
"def print_chart(ticker_series, title=\"\", ylabel=\"Price $\"):\n",
" ax = ticker_series[\"average\"].plot(figsize=(18, 7))\n",
" ax.xaxis_date()\n",
" ax.plot(ticker_series.index, ticker_series['average'], lw=2)\n",
"\n",
" max_acquired = ticker_series['total'].max()\n",
"\n",
" # draw markers onto price time series. Marker size correlates to news volume.\n",
" for index, row in ticker_series.iterrows():\n",
" if row['total'] == 0:\n",
" continue\n",
"\n",
" markersize = (row['total'] / max_acquired) * 25\n",
"\n",
" if markersize < 7:\n",
" markersize = 7\n",
"\n",
" ax.plot([index], \n",
" [row['average']], \n",
" marker='o', \n",
" color='red', \n",
" markersize=markersize)\n",
" \n",
" # overlay arrow pointer at largest news volume \n",
" if row['total'] == max_acquired:\n",
" ax.annotate(\n",
" '\\n' + \"$ {:,.0f}\".format(row['total']),\n",
" xy=(index, row['average']), xycoords='data',\n",
" xytext=(0, -30), textcoords='offset pixels',\n",
" arrowprops=dict(arrowstyle=\"->\", connectionstyle=\"arc3\", color='red')\n",
" )\n",
"\n",
" ax.set_ylabel(ylabel)\n",
" ax.set_xlabel('Day')\n",
" ax.set_title(title)\n",
"\n",
" total = ticker_series['total'].sum()\n",
" text_y_pos = (ticker_series['average'].max() + ticker_series['average'].min()) / 2\n",
" ax.annotate(\n",
" 'Total amount: ' + \"$ {:,.0f}\".format(total),\n",
" xy=(ticker_series.index[10], text_y_pos), xycoords='data',\n",
" xytext=(0, -30), textcoords='offset pixels',\n",
" )\n",
"\n",
" plt.setp(plt.gca().get_xticklabels(), rotation = 0, ha='center')\n",
" plt.show()"
],
"metadata": {
"id": "rzQG6Uf34tKF"
},
"execution_count": 39,
"outputs": []
},
{
"cell_type": "code",
"source": [
"print_chart(oxy_all, \"Buffet's OXY Stock Purchases on Daily Chart in 2018 - 2022\", \"OXY Stock Price ($)\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 430
},
"id": "0D_1AAiS45Jb",
"outputId": "81aa2fe0-6ce8-4ddc-eb14-1534b64920ae"
},
"execution_count": 40,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1296x504 with 1 Axes>"
],
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\n"
},
"metadata": {}
}
]
},
{
"cell_type": "markdown",
"source": [
"Plotting Elon Musk’s insider sales onto Tesla’s daily price chart only requires adding an additional cleaning step."
],
"metadata": {
"id": "EYqH4FyaX38O"
}
},
{
"cell_type": "code",
"source": [
"import numpy as np \n",
"\n",
"tsla_price = pd.read_csv('/content/drive/MyDrive/Colab Notebooks/insider-trading-monitor/TSLA.csv')\n",
"tsla_price['date'] = pd.to_datetime(tsla_price['date'])\n",
"tsla_price = tsla_price[(tsla_price[\"date\"]>=datetime(2019, 1, 1))]\n",
"# remove one incorrect data point\n",
"tsla_index_filter = tsla_price[tsla_price['average'] > 700].index\n",
"tsla_price.drop(tsla_index_filter , inplace=True)\n",
"tsla_price = tsla_price.set_index('date')\n",
"\n",
"tsla_filter = (all_trades[\"issuerTicker\"]==\"TSLA\") & \\\n",
" (all_trades[\"acquiredDisposed\"]==\"D\") & \\\n",
" (all_trades[\"periodOfReport\"]>=datetime(2019, 1, 1)) & \\\n",
" (all_trades[\"reportingPerson\"].str.contains(\"Elon\"))\n",
"\n",
"tsla_disposed = all_trades[tsla_filter].groupby(\"periodOfReport\")[\"total\"].sum()\n",
"tsla_disposed.index.names = ['date']\n",
"tsla_all = pd.merge(tsla_price, tsla_disposed, on='date', how='outer').fillna(0).sort_values(by='date')\n",
"\n",
"# sometimes \"periodfOfReport\" represents a Saturday, but price data isn't available\n",
"# for such days because the market is closed. so, we forward-fill such values.\n",
"tsla_all['average'] = tsla_all['average'].replace(0, np.nan).ffill(axis ='rows')\n",
"\n",
"print_chart(tsla_all, \"Elon Musk Insider Sales on Daily Chart, 2019 - 2022\", \"TSLA Stock Price ($)\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 430
},
"id": "eP7qd6-x46UB",
"outputId": "6273787f-6dc7-4b87-eae3-d35fb30ec857"
},
"execution_count": 41,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1296x504 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
]
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"# Sector statistics\n",
"\n",
"Analyzing insider activity across sectors is the last chapter of this tutorial. We continue with creating a new dataframe called `sector_trades`, which is a copy of the `all_trades` dataframe. The new dataframe only includes the columns `sector`, `total`, `periodOfReport` and `acquiredDisposed`. It then filters out any rows that have an empty value in the `sector` column. The values in the column named `periodOfReport` are then converted to a datetime format and set as the index for `sector_trades`."
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"sector_trades = all_trades[['sector', 'total', 'periodOfReport', 'acquiredDisposed']].copy()\n",
"sector_trades.head(4)\n",
"sector_trades = sector_trades[sector_trades[\"sector\"] != \"\"]\n",
"sector_trades['periodOfReport'] = pd.to_datetime(sector_trades['periodOfReport'])\n",
"sector_trades = sector_trades.set_index('periodOfReport')\n",
"sector_trades.groupby([pd.Grouper(freq='Y'), \"acquiredDisposed\", \"sector\"]).head(5)"
],
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"id": "8-MqfyZC5Kh1",
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"outputId": "a3a64575-fe6f-41f2-8500-1e4db2f341c5"
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"execution_count": 42,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"<ipython-input-42-bdd100419976>:4: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" sector_trades['periodOfReport'] = pd.to_datetime(sector_trades['periodOfReport'])\n"
]
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" sector total acquiredDisposed\n",
"periodOfReport \n",
"2012-01-01 Healthcare 400 A\n",
"2012-01-01 Healthcare 160000000 A\n",
"2012-01-01 Consumer Defensive 5021 D\n",
"2012-01-01 Consumer Defensive 5999 D\n",
"2012-01-01 Consumer Defensive 5232 D\n",
"... ... ... ...\n",
"2022-01-03 Communication Services 15540 A\n",
"2022-01-03 Communication Services 500 A\n",
"2022-01-03 Communication Services 1042 A\n",
"2022-01-03 Communication Services 625 A\n",
"2022-01-03 Communication Services 401 A\n",
"\n",
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{
"cell_type": "markdown",
"source": [
"Using pandas `unstack()` function allows us to create a more readable data structure for plotting stacked bar charts."
],
"metadata": {
"id": "A3uSAlcDYTuP"
}
},
{
"cell_type": "code",
"source": [
"sector_trades[sector_trades[\"acquiredDisposed\"]==\"D\"] \\\n",
" .groupby([pd.Grouper(freq='Y'), \"acquiredDisposed\", \"sector\"])['total'] \\\n",
" .sum() \\\n",
" .unstack()"
],
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"sector Basic Materials Communication Services \\\n",
"periodOfReport acquiredDisposed \n",
"2012-12-31 D 9797499803 5841613169 \n",
"2013-12-31 D 9251198777 1379323263 \n",
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"\n",
"sector Consumer Cyclical Consumer Defensive \\\n",
"periodOfReport acquiredDisposed \n",
"2012-12-31 D 24313930860 21855654495 \n",
"2013-12-31 D 50673768601 12433221422 \n",
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"\n",
"sector Energy Financial Services Healthcare \\\n",
"periodOfReport acquiredDisposed \n",
"2012-12-31 D 32262645372 21539322289 18339774792 \n",
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"\n",
"sector Industrials Real Estate Technology \\\n",
"periodOfReport acquiredDisposed \n",
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"sector Utilities \n",
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" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>\n",
" <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-88c20dea-6124-4fb9-9e0a-8b913f56b9c7')\"\n",
" title=\"Convert this dataframe to an interactive table.\"\n",
" style=\"display:none;\">\n",
" \n",
" <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
" width=\"24px\">\n",
" <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
" <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
" </svg>\n",
" </button>\n",
" \n",
" <style>\n",
" .colab-df-container {\n",
" display:flex;\n",
" flex-wrap:wrap;\n",
" gap: 12px;\n",
" }\n",
"\n",
" .colab-df-convert {\n",
" background-color: #E8F0FE;\n",
" border: none;\n",
" border-radius: 50%;\n",
" cursor: pointer;\n",
" display: none;\n",
" fill: #1967D2;\n",
" height: 32px;\n",
" padding: 0 0 0 0;\n",
" width: 32px;\n",
" }\n",
"\n",
" .colab-df-convert:hover {\n",
" background-color: #E2EBFA;\n",
" box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
" fill: #174EA6;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-convert {\n",
" background-color: #3B4455;\n",
" fill: #D2E3FC;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-convert:hover {\n",
" background-color: #434B5C;\n",
" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
" fill: #FFFFFF;\n",
" }\n",
" </style>\n",
"\n",
" <script>\n",
" const buttonEl =\n",
" document.querySelector('#df-88c20dea-6124-4fb9-9e0a-8b913f56b9c7 button.colab-df-convert');\n",
" buttonEl.style.display =\n",
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
"\n",
" async function convertToInteractive(key) {\n",
" const element = document.querySelector('#df-88c20dea-6124-4fb9-9e0a-8b913f56b9c7');\n",
" const dataTable =\n",
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
" [key], {});\n",
" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
" dataTable['output_type'] = 'display_data';\n",
" await google.colab.output.renderOutput(dataTable, element);\n",
" const docLink = document.createElement('div');\n",
" docLink.innerHTML = docLinkHtml;\n",
" element.appendChild(docLink);\n",
" }\n",
" </script>\n",
" </div>\n",
" </div>\n",
" "
]
},
"metadata": {},
"execution_count": 43
}
]
},
{
"cell_type": "markdown",
"source": [
"The corresponding logic to plot the unstacked data is described in `print_sector_stats()`."
],
"metadata": {
"id": "2rtsTWJLYYGT"
}
},
{
"cell_type": "code",
"source": [
"def print_sector_stats(trades, title=\"Acquisition Distribution per Sector per Year\"):\n",
" df = trades.groupby([pd.Grouper(freq='Y'), \"acquiredDisposed\", \"sector\"])['total'].sum()\n",
"\n",
" fig, ax = plt.subplots()\n",
"\n",
" unstacked = df.unstack()\n",
" unstacked.plot.bar(stacked=True, ax=ax, figsize=(17, 10))\n",
"\n",
" ax.legend(loc=2)\n",
"\n",
" ax.grid(True)\n",
" ax.yaxis.set_major_formatter(matplotlib.ticker.FuncFormatter(millions_formatter))\n",
" ax.set_xticks(range(unstacked.index.size))\n",
" ax.set_xticklabels([idx[0].strftime('%Y') for idx in unstacked.index])\n",
" ax.figure.autofmt_xdate(rotation=0, ha='center')\n",
" ax.set_xlabel(\"Year\")\n",
" ax.set_ylabel(\"Amount $\")\n",
" ax.set_title(title)\n",
"\n",
" plt.show()"
],
"metadata": {
"id": "bk5LJdZT6Ihj"
},
"execution_count": 44,
"outputs": []
},
{
"cell_type": "code",
"source": [
"print_sector_stats(sector_trades[sector_trades[\"acquiredDisposed\"]==\"A\"], \"Insider Buy Distribution per Sector per Year\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 576
},
"id": "Zwvf1ytH6Ooc",
"outputId": "4e8f9c1d-2ffa-44df-fce2-b07d3a76d2d9"
},
"execution_count": 45,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1224x720 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
]
},
{
"cell_type": "code",
"source": [
"print_sector_stats(sector_trades[sector_trades[\"acquiredDisposed\"]==\"D\"], \"Insider Sales Distribution per Sector per Year\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 576
},
"id": "m_bMh66u6Pv0",
"outputId": "faac53da-256f-44d6-ffe1-8388219a6d94"
},
"execution_count": 46,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1224x720 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {}
}
]
},
{
"cell_type": "markdown",
"source": [
"# Conclusion\n",
"\n",
"Wow, if you stayed with me up until now, you’re truly interested in this topic. In summary, we learned how to access all insider transactions disclosed over the last decade and analyze the data using various techniques, such as daily chart overlay plots.\n",
"\n",
"Keep in mind that the approach discussed has some weaknesses. For example, we ignored all derivative transactions in our analysis. Usually, derivative transactions include issuance of options with \\$0 price tags attached. However, there might be some transactions with >$0 prices that we didn’t consider. Also, the price per share vs total amount of transaction discrepancy isn’t 100% solved. We would have to check the share price at each transaction date in order to ensure the correctness of the reported transaction price and, if necessary, convert the total price to its price per share equivalent. Also, a change of ticker symbol was not considered in our analysis. For example, an insider might disclose a Form 4 with ticker ABC, company ABC changes its ticker to XYZ, and insider discloses another Form 4 with ticker XYZ. The two disclosed transactions are not linked anymore and would be classified as one insider, trading two different stocks."
],
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"source": [
"# Other Relevant Filings\n",
"\n",
"- [Form 13D](https://www.ecfr.gov/current/title-17/chapter-II/part-240/section-240.13d-1#p-240.13d-1(a)) has to be filed 10 days after the acquisition of more than 5% ownership of the company. Person can choose to file Form 13G instead if no control over company is wanted.\n",
"- [Form 13G](https://www.ecfr.gov/current/title-17/chapter-II/part-240/section-240.13d-1#p-240.13d-1(b)(2)) has to be filed 45 days after the end of the calendar year and is intended for investors not wanting to change/influence the control of the company. For example, brokers, banks and investment adviers. If the ownership exceeds 10%, Form 13G has to be filed within 10 days after the month of acquisition. Person has to file Form 13D instead if ownership exceeds 20% or if person wants to control the company.\n",
"- [Form 13F](https://www.ecfr.gov/current/title-17/chapter-II/part-240/section-240.13f-1) is filed by institutional investment managers managing $100M+ AUM on a quarterly schedule, and discloses all holdings of the managers."
],
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},
{
"cell_type": "markdown",
"source": [
"# Papers about insider trading\n",
"\n",
"[SEC Rule 10b5-1 and insiders’ strategic trade](https://bradreese.com/blog/6-28-2012.pdf)\n",
"\n",
"[Offensive Disclosure: How Voluntary Disclosure Can Increase Returns from Insider Trading](https://chicagounbound.uchicago.edu/cgi/viewcontent.cgi?article=12130&context=journal_articles)\n",
"\n",
"[Decoding Inside Informatio](https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1540-6261.2012.01740.x)\n",
"\n",
"[Do SEC’s 10b5-1 Safe Harbor Rules Need To Be Rewritten?](https://journals.library.columbia.edu/index.php/CBLR/article/view/1734)\n",
"\n",
"[SEC Rule 10b5-1 Plans and Strategic Trade around Earnings Announcements](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2880878)\n",
"\n",
"[Insider sales based on short-term earnings information](https://ideas.repec.org/a/kap/rqfnac/v47y2016i1d10.1007_s11156-014-0496-7.html)"
],
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"cell_type": "markdown",
"source": [
"# References\n",
"\n",
"- https://www.sec.gov/rules/other/34-46313.htm\n",
"- https://www.law.cornell.edu/cfr/text/17/240.16a-1\n",
"- https://www.law.cornell.edu/cfr/text/17/240.16a-2\n",
"- https://www.ecfr.gov/current/title-17/chapter-II/part-240/subject-group-ECFR4594b28bbb3a5d5/section-240.16a-2\n",
"- https://www.law.cornell.edu/uscode/text/15/78p\n",
"- https://www.law.cornell.edu/uscode/text/15/80a-29\n",
"- https://www.law.cornell.edu/cfr/text/17/240.16b-3\n",
"- https://www.investopedia.com/terms/s/section-16.asp\n",
"- https://www.investopedia.com/terms/s/shortswingprofitrule.asp\n",
"- https://www.sec.gov/divisions/corpfin/guidance/sec16interp\n",
"- https://www.law.cornell.edu/cfr/text/12/163.172\n",
"- https://www.cfainstitute.org/en/advocacy/issues/derivatives\n",
"- https://www.law.cornell.edu/cfr/text/17/240.10b-5\n",
"- https://www.ecfr.gov/current/title-17/chapter-II/part-240/subpart-A#240.10b-5\n",
"- https://www.sec.gov/rules/final/33-7881.htm\n",
"- https://www.akingump.com/en/news-insights/sec-amendments-regarding-rule-10b5-1-insider-trading-plans-and-related-disclosures.html\n",
"- https://www.federalregister.gov/documents/2022/12/29/2022-27675/insider-trading-arrangements-and-related-disclosures\n",
"- https://www.ecfr.gov/current/title-17/chapter-II/part-240/section-240.13d-101\n",
"- https://www.ecfr.gov/current/title-17/chapter-II/part-240/section-240.13d-102\n",
"- https://www.ecfr.gov/current/title-17/chapter-II/part-240/section-240.13d-1#p-240.13d-1(a)\n",
"- https://www.law.cornell.edu/cfr/text/17/240.16a-13\n",
"\n",
"\n",
"\n"
],
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"id": "AWgtHStoZ0Ro"
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}
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