Interactive Brokers API Tutorial (Beginners)

Welcome and Reflection on 2020

The speaker welcomes the audience back, acknowledges the challenges of 2020, particularly in financial markets, and expresses gratitude for the growth of the channel.

Reflection on 2020

• The year 2020 has been exceptional for trading and investing, marking significant gains for many individuals.

• Introduction to Interactive Brokers as a platform with a public API, catering to a professional audience.

• Background of Interactive Brokers: founded in 1977 by Thomas Peterffy, known for pioneering algorithmic trading systems.

• Thomas Peterffy's journey from Hungary to becoming a computer programmer and his innovative contributions to automated trading.

Exploring Interactive Brokers

Delving into the history and functionalities of Interactive Brokers, highlighting its significance in the world of trading platforms.

Interactive Brokers Insights

• Thomas Peterffy's creation of the first algorithmic trading system in 1987 revolutionized trading processes.

• Overcoming obstacles such as Nasdaq banning direct interfaces through creative solutions like using cameras for data decoding.

• Thomas Peterffy's entrepreneurial success story leading him to become one of Florida's wealthiest individuals.

Pros and Cons Analysis

Evaluating Interactive Brokers from a user perspective by discussing both positive aspects and drawbacks of the platform.

Platform Evaluation

• Critique on user interface: perceived as outdated compared to modern apps like Robinhood or Alpaca.

• User experience challenges due to an interface that may appear archaic and less intuitive than contemporary platforms.

Interactive Brokers: Fees, Ease of Use, and Advantages

In this section, the speaker discusses the fees associated with using Interactive Brokers, the challenges related to its ease of use, and highlights some advantages of the platform.

Fees Associated with Interactive Brokers

• The speaker mentions that there are various fees involved in using Interactive Brokers, including fees for executing trades and data subscriptions.

• To access real-time streaming data and historical data on Interactive Brokers, users need to pay a monthly fee which can amount to around $15 initially.

• Users should be aware that if they do not use their account at all, there is a possibility of being charged $20 per month. To avoid this fee, maintaining a high balance or executing a certain amount of commission in trades is necessary.

Challenges with Ease of Use

• The speaker shares his experience of finding Interactive Brokers confusing initially due to the complex setup process involving downloading TWS workstation and IB Gateway. This complexity made it challenging even for an experienced programmer.

• Understanding how to program on Interactive Brokers was also daunting as it required dealing with multi-threaded network programming and implementing specific classes/interfaces.

Advantages of Interactive Brokers

• Despite its complexities, one advantage highlighted is that Interactive Brokers is global in scope compared to other platforms like Alpaca which may have limitations in international use.

• Another significant advantage is the wide range of markets (135), countries (33), and currencies (23) supported by Interactive Brokers. Users have the flexibility to trade various securities including options, futures, foreign exchange trading across different regions.

Detailed Comparison of Trading Platforms

In this section, the speaker discusses the differences between various trading platforms, focusing on Alpaca and Trade Ear, highlighting the limitations of some newer APIs designed by less experienced individuals compared to established platforms like Interactive Brokers.

Alpaca vs. Trade Ear

• Newer APIs like Alpaca lack support for options trading, unlike more established platforms.

• Platforms designed by younger individuals may offer sleek user interfaces but lack the depth of features and experience found in traditional platforms like Interactive Brokers.

• Order execution quality is a crucial factor; Interactive Brokers excels in this aspect by not selling order flow data, unlike commission-free brokerages such as Robinhood.

• As traders become more serious, factors like order execution speed and price become increasingly important, favoring platforms like Interactive Brokers over newer alternatives.

• Interactive Brokers offers a wide range of order types (e.g., 68 order types), catering to professional traders' diverse needs.

Advantages of Interactive Brokers for Professional Traders

This part delves into the advanced features offered by Interactive Brokers that cater to professional traders' requirements, emphasizing tools like research capabilities and extensive charting options.

Features for Professional Traders

• Interactive Brokers provides essential professional tools such as bracket orders and trailing stops that are crucial for experienced traders.

• The platform offers comprehensive research tools including scanners for stock selection based on specific criteria and fundamental analysis metrics.

• While lacking modern mobile features like push notifications seen in newer platforms, Interactive Brokers excels in providing built-in charting tools with indicators for technical analysis.

Interactive Brokers: A Comprehensive Trading Platform

This segment highlights how Interactive Brokers stands out due to its all-in-one approach with built-in tools such as charting options and paper trading API while comparing it to other platforms lacking similar functionalities.

Comprehensive Platform Features

• Unlike some platforms requiring supplementary apps for advanced charting needs, Interactive Brokers integrates built-in charting tools with indicators within its platform.

• The availability of a paper trading API sets Interactive Brokers apart from competitors like TD Ameritrade that lack this essential feature for algorithm testing before live deployment.

Considerations When Choosing a Trading Platform

The speaker provides insights into factors influencing the choice of a trading platform, emphasizing considerations such as fees, data quality, order execution efficiency, and learning curve associated with each platform.

Factors Influencing Choice

• Opting for Interactive Brokers is recommended if willing to pay fees for superior data quality, robust order execution capabilities, and comprehensive tools despite the initial learning curve.

Exploring IBN Sync Library with Python

This part focuses on practical application by exploring the IBN Sync library using Python to delve into real-time market interactions before market closure on December 31st.

Practical Application with IBN Sync Library

Setting Up Interactive Brokers API

In this section, the speaker discusses setting up the Interactive Brokers API by creating a requirements.txt file and installing necessary packages.

Creating Requirements.txt and Installing Packages

• Installing ib_insync package using pip install ib_insync.

• The package is essential for connecting to Interactive Brokers.

• Setting up the environment for running the demo app.

Connecting to Interactive Brokers

This part focuses on connecting to Interactive Brokers by importing classes and functions and establishing a connection through network socket communication.

Importing Classes and Functions

• Importing classes and functions from ib_insync using from ib_insync import *.

• Creating a new instance of the IB class to connect to Interactive Brokers.

• Initiating the connection by calling the connect method with specific parameters like IP address, port number, and client ID.

Interactive Brokers Setup

Exploring how Interactive Brokers operates differently from other trading platforms through network socket connections rather than web API requests.

Operating Mechanism of Interactive Brokers

• Utilizing network socket connections instead of web API requests.

• Needing to download either Trader Workstation or IB Gateway for communication with servers.

• Contrasting features between Trader Workstation (full interface) and IB Gateway (lightweight application).

Trader Workstation Configuration

Configuring Trader Workstation settings for API access, including enabling permissions and specifying socket port numbers.

Configuring Trader Workstation Settings

• Enabling necessary permissions like submitting orders in addition to retrieving data.

• Adjusting settings such as socket port number based on whether using IB Gateway or Trader Workstation.

Interactive Brokers Tutorial

In this section, the speaker introduces how to work with Interactive Brokers by setting up symbols for trading and specifying currencies.

Setting Up Symbols and Currencies

• Symbol setup involves assigning a symbol to an exchange, often using "smart" for Interactive Brokers' smart routing.

• Currency selection is crucial; while the default is U.S. dollars, multiple currencies are supported for trading.

Requesting Historical Data

This part covers requesting historical data using Interactive Brokers and Python.

Requesting Historical Data

• Initiating historical data retrieval by calling methods on the ib object and specifying parameters like stock contract, end time, duration, and bar size setting.

• Understanding the significance of parameters such as end time in determining the historical data range retrieved.

Analyzing Historical Data

Analyzing historical data retrieved from Interactive Brokers using Python.

Analyzing Data

• Configuring parameters like bar size setting to determine granularity (e.g., hourly bars) of historical data retrieved.

• Exploring options like specifying what to show (e.g., midpoint) when constructing bars from historical data.

Converting Data to DataFrame

Converting bar data obtained from Interactive Brokers into a Pandas DataFrame for easier analysis.

Data Conversion Process

• Utilizing the util utility provided by Interactive Brokers to convert bar data objects into a structured Pandas DataFrame format.

• Demonstrating how converting raw bar data into a DataFrame enhances readability and facilitates further analysis of financial information.

Real-Time Data Retrieval

Exploring real-time data retrieval capabilities with Interactive Brokers through Python programming.

Real-Time Data Access

• Transitioning from historical to real-time market data retrieval by leveraging functions within Interactive Brokers' library.

• Highlighting asynchronous nature of real-time market data requests and potential delays in receiving live ticker updates for analysis.

Understanding Asynchronous Programming

In this section, the speaker explains the concept of asynchronous programming and its benefits compared to synchronous programming.

Asynchronous vs. Synchronous Programming

• Asynchronous programming allows a program to continue executing other tasks while waiting for a request to finish.

• Programs that block require the program to stop and wait for a request to complete.

• Requests in asynchronous programming happen concurrently, enabling the CPU to perform other tasks while waiting for data retrieval.

• Multiple tasks can be executed simultaneously, enhancing efficiency.

• By firing off multiple asynchronous requests, programs can finish quicker than traditional synchronous methods.

• Example of using asynchronous functionality provided by Rich Wheels is highlighted.

Real-world Example: Chess Exhibition

The speaker presents a real-world analogy involving chess exhibition to illustrate the efficiency of asynchronous processing.

Chess Exhibition Analogy

• An analogy is drawn with a chess exhibition where a player competes against multiple opponents sequentially.

• Comparison made between waiting for opponents' moves sequentially versus making moves asynchronously.

• By playing against opponents concurrently, the player significantly reduces the time required to complete all games.

• Explanation on how parallel processing optimizes time management in gaming scenarios.

Implementing Callback Functions

The discussion shifts towards implementing callback functions in interactive brokers (IB) sync for event handling.

Callback Functions in IB Sync

• Callback functions are used in IB sync to respond to specific events such as new orders or account changes.

• Events like pending tickers trigger defined functions upon updates or executions.

• Subscribing to events allows programmers to execute code without waiting for responses, enhancing program flow and responsiveness.

Javascript Callback Functions

In this section, the speaker discusses the concept of callback functions in JavaScript and how they are used to handle asynchronous operations.

Understanding Callback Functions

• The speaker introduces the pending tickers event and demonstrates how to attach a callback function named on pending tickers to it.

• The defined on pending tickers function receives ticker data and prints a message when new data is received.

• Upon running the program, an error occurs as the callback function is not defined, highlighting the importance of proper function definition for event handling.

Implementing Continuous Program Execution

• To ensure continuous program execution, the speaker introduces ib.run to keep the program running in a loop, allowing for event handling even after initial execution.

• Running the program with continuous execution showcases real-time data retrieval and processing through callback functions attached to events.

Real-Time Data Handling

• The speaker emphasizes passing callback functions for real-time data processing, showcasing how new data triggers these functions repeatedly.

• Despite demonstrating appending data to a pandas dataframe as an example, time constraints lead to focusing on historical and real-time data retrieval instead.

Placing Orders with Interactive Brokers

This segment delves into placing orders using Interactive Brokers API, covering order creation, connection establishment, and order submission processes.

Creating Order Objects

• The speaker sets up a stock contract object and establishes a connection with Interactive Brokers workstation or gateway for order placement.

• Introduction of an order object requiring specifications such as type (e.g., limit order), action (buy/sell), quantity (shares), and price for trade execution.

Executing Buy Order

• Demonstrating creating a limit buy order for AMD stock with specific quantity and price parameters set within the code.

• After creating the order object, connecting it with the stock contract using ib.place_order method ensures actual submission of the buy order for execution.

Monitoring Order Status

• Upon placing the trade order, notifications indicate successful submission; however, asynchronous processing implies that immediate fulfillment may not occur despite notification display.

New Section

In this section, the speaker discusses subscribing to events and receiving callbacks when orders are filled in a program.

Subscribing to Events and Callbacks

• Subscribing to an event allows for receiving a callback when an order is filled.

• By tapping into the "on fill" event in the API documentation, one can set up callbacks for order fills.

• The callback function for order filled receives parameters related to the trade and fill, enabling actions like printing details upon order completion.

• Running the program continuously using ib.run ensures that callbacks can be received even after placing orders.

• Utilizing callback functions enables concurrent processing in a single thread, enhancing program efficiency without constant polling for updates.

Exploring Order Placement and Callback Functions

This segment delves into executing orders, utilizing callback functions effectively, and handling trade history.

Executing Orders with Callback Functions

• Demonstrates placing market orders for stocks like Apple using callback functions for order completion notifications.

• Engaging in paper trading mode allows testing strategies without financial risk while still experiencing real-time trade execution.

• Retrieving all placed orders and trades through functions like ib.order provides insights into trading history for analysis.

Analyzing Trade Execution and History

This part focuses on reviewing executed trades, understanding fill prices, and managing historical data efficiently.

Reviewing Executed Trades

• Examining executed trades reveals details such as fill prices, quantities traded, and timestamps of transactions.

• Understanding how limit and market orders work alongside utilizing callbacks enhances trade execution strategies effectively.

Utilizing Options Data: An Example

Exploring options data retrieval through IB's functionalities provides insights into expanding trading capabilities.

Accessing Options Data

• Requesting option chain data via IB's functionality expands trading possibilities beyond traditional stock investments.

New Section

In this section, the speaker discusses setting parameters for a symbol, security type, and contract ID to obtain option chain data.

Setting Parameters for Option Chain Data

• Parameters include assigning a symbol (e.g., "apple"), specifying the security type as stock, and providing a contract ID obtained through the function ib.qualify contracts on stock.

• Running ib.qualify contracts generates a contract ID necessary for requesting option chain data.

• To access option chain data, use the contract ID in defining chains with ib.security option params stock.

New Section

This segment covers handling errors during network programming and refining parameter settings for obtaining option chain data.

Error Handling and Parameter Refinement

• Emphasizes the importance of gracefully handling disconnections during network programming to ensure uninterrupted functionality.

• Adjusting parameters like security type based on existing object references rather than hard-coding values enhances accuracy in retrieving desired data.

New Section

Exploring the conversion of retrieved data into a structured format using utility functions for improved readability.

Data Conversion and Visualization

• Utilizing util df to convert retrieved data into a dataframe format for enhanced visualization and analysis.

• Examining option chain details such as expiration dates, strike prices, call/put distinctions, and premiums within the converted dataframe format.

New Section

Delving into placing orders on options derived from option chains and preparing to explore scanner features.

Order Placement and Scanner Features

• Discusses potential order placement on specific options extracted from option chains for executing an option order.

• Introduces utilizing scanner features like fundamentals.pi to gather detailed information about specific instruments such as stocks.

New Section

Demonstrating how to request fundamental data about particular instruments using blocking functions like request fundamental data.

Requesting Fundamental Data

• Initiating requests for fundamental data on selected instruments by employing functions like request fundamental data with specified report types.

Fundamental Data Extraction Using Beautiful Soup

In this section, the speaker demonstrates how to extract fundamental data using Beautiful Soup library in Python.

Extracting Fundamental Data

• Import Beautiful Soup by using from bs4 import BeautifulSoup as bs.

• Create a Beautiful Soup object by passing the markup string to access XML documents as objects or dictionaries.

• Utilize data structures provided by Beautiful Soup to interact with XML documents effectively.

• Find and print specific ratios from the XML document by using content.find_all('ratio').

• Print both the field name and ratio text to add additional meaning to the extracted data.

Scanner Functionality for Stock Screening

The speaker introduces scanner functionality for stock screening purposes within Interactive Brokers platform.

Scanner Functionality

• Demonstrate scanner functionality similar to a screener for stock screening.

• Define instrument type and location code for scanning specific stocks of interest.

• Use scan codes like "current year etf dividend yield descending" to filter ETFs based on high dividend yields.

Interactive Brokers - Scanners and Market Closing

In this section, the speaker demonstrates how to access various scanners using Interactive Brokers and provides insights on market closing trends.

Accessing Scanners

• The speaker showcases accessing scanners by calling ib.requestScannerParameters() to retrieve all available parameters for scanning.

• By outputting the parameters to a text file named scanners.txt, a comprehensive list of scan options such as bonds and percentages is obtained.

Market Closing Trends

• The speaker mentions the imminent market closure at 1 pm, highlighting that both Dow Jones and S&P 500 are reaching all-time highs.

• Despite initial downward trends, there is a notable market rebound with Dow Jones achieving an all-time record along with positive performance across the board.

Closing Remarks

• As the markets close for the year, it is noted that it marks the final trading day of the year. The speaker hints at potential future videos in 2021 exploring Interactive Brokers further.