Algorithmic Trading using Interactive Brokers Python API

Implement algorithmic trading strategies on Interactive Broker’s platform
Algorithmic Trading using Interactive Brokers Python API
File Size :
6.91 GB
Total length :
11h 45m

Category

Instructor

Mayank Rasu

Language

Last update

Last updated 11/2022

Ratings

4.4/5

Algorithmic Trading using Interactive Brokers Python API

What you’ll learn

Algorithmic Trading
Interactive Broker API
Quantitative Finance
Advanced Python Concepts

Algorithmic Trading using Interactive Brokers Python API

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

You Can See More Courses in the Business >> Greetings from CourseDown.com

New Courses

Scroll to Top