Algorithmic Trading using Interactive Brokers Python API
What you’ll learn
Algorithmic Trading
Interactive Broker API
Quantitative Finance
Advanced Python Concepts
Requirements
Interactive Broker Account
Basic python skills (should be familiar with data types, data structures, loops, functions, installing and importing libraries etc.)
Intermediate level familiarity with finance/trading
Description
Design and deploy trading strategies on Interactive Broker’s platform. Automate every step of your strategy including, extracting data (stock data and fundamental data), performing technical/fundamental analysis, generating signals, placing trades, risk management etc. Gain a thorough understanding of native interactive broker’s API.You can expect to gain the following skills from this courseAPI tradingAdvanced python concepts (OOP concepts, multi-threading etc.) Extracting historical dataExtracting fundamental dataHarnessing streaming tick level dataIncorporating technical indicators using pythonEnd to End strategy design and deploymentHandling asynchronous callsSqlite database managementInteractive Broker’s TWS terminalRelevant account settings in IB#############################################################################################Important note – Course prerequisites:Please note that this course requires basic python proficiency. At the minimum, you should be comfortable with:basic python data types and formatbasic python data structures such as list, dictionary, tuple etc. how to create python functionshow to implement loops in pythoninstalling and importing libraries Basic python proficiency is mandatory because Interactive Broker API’s python client uses advanced OOP and asynchronous programming concepts. While, I have devoted an entire section explaining these concepts, students with no python knowledge will really struggle to follow along.#############################################################################################
Overview
Section 1: Introduction to Interactive Brokers & its API
Lecture 1 IB TWS Introduction
Lecture 2 IB API Architecture
Lecture 3 Anaconda Distribution Intro
Lecture 4 Creating Virtual Environment (Optional)
Lecture 5 Installing IB Python Client
Lecture 6 API Configuration Settings
Section 2: Advanced Python Concepts
Lecture 7 OOP Basics (Class – I)
Lecture 8 OOP Basics (Class – II)
Lecture 9 OOP Basics (Inheritance)
Lecture 10 Threads in Python
Lecture 11 Turning “Daemon” Threads into Your Angel
Lecture 12 Multi threading using Event object
Lecture 13 Websocket Intro
Section 3: Understanding IB API Python Wrapper
Lecture 14 Eclient and Ewrapper Class Intro
Lecture 15 Getting Contract Info
Lecture 16 Asynchronous Implementation Intro
Lecture 17 Asynchronous Implementation Using Event
Section 4: Historical Data
Lecture 18 Market Data Subscription
Lecture 19 Important Note: Please Read
Lecture 20 Getting Historical Data Using IBAPI
Lecture 21 Getting Historical Data (multiple tickers) using IBAPI
Lecture 22 Storing Historical Data in Dataframes
Lecture 23 Storing Historical Data in Dataframes – II
Lecture 24 Extracting Historical Data Iteratively
Lecture 25 Storing Historical Data of Stocks from Different Exchanges
Section 5: Order Management
Lecture 26 Placing a Simple Limit Order Using IBAPI
Lecture 27 Placing Order – Reusable Code
Lecture 28 Cancelling Orders
Lecture 29 Modifying Orders
Lecture 30 Other Important Order Types
Section 6: Other Important API Calls
Lecture 31 Getting Open Orders Information
Lecture 32 Getting Position Details
Lecture 33 Homework – Getting Account Summary & PnL Details
Lecture 34 Homework Solution
Section 7: Technical Indicators in IB
Lecture 35 Technical Indicators Intro
Lecture 36 TWS Terminal – Technical Indicators
Lecture 37 MACD Overview
Lecture 38 MACD Implementation Using IBAPI
Lecture 39 ATR and Bollinger Bands Overview
Lecture 40 Bollinger Bands Implementation Using IBAPI
Lecture 41 ATR Implementation Using IBAPI
Lecture 42 RSI Overview and Excel Implementation
Lecture 43 RSI Implementation Using IBAPI
Lecture 44 ADX Overview
Lecture 45 ADX Implementation in Excel
Lecture 46 ADX Implementation Using IBAPI
Lecture 47 Stochastic Oscillator Overview
Lecture 48 Stochastic Oscillator Implementation Using IBAPI
Section 8: Backtesting Strategies
Lecture 49 Backtesting Intro
Lecture 50 CAGR Implementation using IBAPI
Lecture 51 Volatility & Sharpe Implementation using IBAPI
Lecture 52 Maximum Drawdown Implementation
Lecture 53 KPIs for Intraday Strategies
Lecture 54 Backtesting Sample Strategy (MACD+Stochastic)
Lecture 55 Backtesting Strategy – Extracting Data
Lecture 56 Backtesting Strategy – Signal Generation & Return Calculation
Lecture 57 Backtesting Strategy – KPI Calculation
Lecture 58 Homework – Implement Intraday KPIs
Lecture 59 Homework Solution
Section 9: Designing & Deploying Strategies on IB
Lecture 60 Strategy Implementation – Blueprint
Lecture 61 Strategy Implementation – Data Preparation
Lecture 62 Strategy Implementation – Signal
Lecture 63 Strategy Execution Demo
Lecture 64 Closing All Positions Programatically
Section 10: Streaming Market Data
Lecture 65 Streaming Tick Level Data
Lecture 66 Streaming Aggregated Snapshot Data – I
Lecture 67 Streaming Aggregated Snapshot Data – II
Lecture 68 Storing Tick Data in SQL DB – I
Lecture 69 Storing Tick Data in SQL DB – II
Lecture 70 Storing Tick Data in SQL DB – III
Lecture 71 Accessing Data in DB
Lecture 72 Converting Ticks to Candles
Section 11: Extracting Fundamental Data
Lecture 73 Fundamental Data API Basics
Lecture 74 Storing Fundamental Data in XML File
Lecture 75 Parsing XML Data – I
Lecture 76 Parsing XML Data – II
Lecture 77 Parsing XML Data – III
Lecture 78 Handling Multiple Fundamental Data Files
Traders looking to automate their strategies on Interactive Broker’s platform,Anyone interested in Algorithmic trading
Course Information:
Udemy | English | 11h 45m | 6.91 GB
Created by: Mayank Rasu
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