Book Image

Getting Started with Forex Trading Using Python

By : Alex Krishtop
Book Image

Getting Started with Forex Trading Using Python

By: Alex Krishtop

Overview of this book

Algorithm-based trading is a popular choice for Python programmers due to its apparent simplicity. However, very few traders get the results they want, partly because they aren’t able to capture the complexity of the factors that influence the market. Getting Started with Forex Trading Using Python helps you understand the market and build an application that reaps desirable results. The book is a comprehensive guide to everything that is market-related: data, orders, trading venues, and risk. From the programming side, you’ll learn the general architecture of trading applications, systemic risk management, de-facto industry standards such as FIX protocol, and practical examples of using simple Python codes. You’ll gain an understanding of how to connect to data sources and brokers, implement trading logic, and perform realistic tests. Throughout the book, you’ll be encouraged to further study the intricacies of algo trading with the help of code snippets. By the end of this book, you’ll have a deep understanding of the fx market from the perspective of a professional trader. You’ll learn to retrieve market data, clean it, filter it, compress it into various formats, apply trading logic, emulate the execution of orders, and test the trading app before trading live.
Table of Contents (21 chapters)
1
Part 1: Introduction to FX Trading Strategy Development
5
Part 2: General Architecture of a Trading Application and A Detailed Study of Its Components
11
Part 3: Orders, Trading Strategies, and Their Performance
15
Part 4: Strategies, Performance Analysis, and Vistas

Index

As this ebook edition doesn't have fixed pagination, the page numbers below are hyperlinked for reference only, based on the printed edition of this book.

A

active trading 5

aggregation 50, 51

algorithmic (algo) 197

algo trading

pros and cons 345, 346

risks 343

alpha 198-200

in investment and trading 306-308

alpha classics 208

breakouts 214-216

mean reversion 210-214

trend following 208-210

arbitrage 5, 51, 216, 217

arbitrage strategies 37

arbitrageurs 51

asset 4

associated risks

profiting 220

automated trading 7

average trade 298, 299

averaging down 342

B

backends 158

backtesting 22, 23, 260, 261

equity curve 269-276

in Python 23

order execution, emulating 266-269

purpose 23

statistics 269-276

threads, syncing with events 261-263

with historical data feed 264-266

bank indices 202-204

bar charts

creating, with mplfinance 175

creating, with...