Python Algorithmic Trading Cookbook

Build a solid foundation in algorithmic trading by developing, testing and executing powerful trading strategies with real market data using Python

▶What You Will Learn
⦁Use Python to set up connectivity with brokers
⦁Handle and manipulate time series data using Python
⦁Fetch a list of exchanges, segments, financial instruments, and historical data to interact with the real market
⦁Understand, fetch, and calculate various types of candles and use them to compute and plot diverse types of technical indicators
⦁Develop and improve the performance of algorithmic trading strategies
⦁Perform backtesting and paper trading on algorithmic trading strategies
⦁Implement real trading in the live hours of stock markets

▶Key Features
⦁Build a strong foundation in algorithmic trading by becoming well-versed with the basics of financial markets
⦁Demystify jargon related to understanding and placing multiple types of trading orders
⦁Devise trading strategies and increase your odds of making a profit without human intervention

▶Who This Book Is For
If you are a financial analyst, financial trader, data analyst, algorithmic trader, trading enthusiast or anyone who wants to learn algorithmic trading with Python and important techniques to address challenges faced in the finance domain, this book is for you. Basic working knowledge of the Python programming language is expected. Although fundamental knowledge of trade-related terminologies will be helpful, it is not mandatory.

▶What this book covers
⦁ Chapter 1, Handling and Manipulating Date, Time, and Time Series Data, explains everything about the Python DateTime module and pandas DataFrames that are required to handle time series data efficiently.

⦁ Chapter 2, Stock Markets – Primer on Trading, covers how to set up Python connectivity with a broker, fetch financial instruments, and get a quick hands-on at placing simple orders. You will also learn how to query margins and calculate brokerage and government taxes.

⦁ Chapter 3, Fetching Financial Data, covers financial instruments in-depth.

⦁ Chapter 4, Computing Candlesticks and Historical Data, explains how to fetch and understand historical data, and also how to fetch, compute, and plot various candlestick patterns, including Japanese (OHLC), Renko, Line Break, and Heikin-Ashi.

⦁ Chapter 5, Computing and Plotting of Technical Indicators, explains how to compute and plot 10 types of technical indicators, including trend indicators, momentum indicators, volatility indicators, and volume indicators.

⦁ Chapter 6, Placing Regular Orders on the Exchange, explains how to place 16 types of regular orders across two transaction types, two order codes, and four order varieties. You will learn how to query the order status in real time, while also learning about the possible order states supported by the broker and the order life cycle for regular orders.

⦁ Chapter 7, Placing Bracket and Cover Orders on the Exchange, explains how to place eight types of bracket orders and four types of cover orders across two transaction types and multiple order varieties and how to query the order status in real time. You will learn about target, stoploss, and trailing stoploss, along with the possible order states supported by the broker and the order life cycle for both bracket and cover orders.

⦁ Chapter 8, Algorithmic Trading Strategies – Code Step by Step, explains how to code your own algorithmic trading strategy from scratch using two strategy coding examples involving regular and bracket orders, respectively.

⦁ Chapter 9, Algorithmic Trading – Backtesting, covers how to backtest your own algorithmic trading strategy using two strategy coding examples involving regular and bracket orders, respectively. You will also learn how to fetch execution logs and various types of backtesting reports, including profit and loss reports, statistics reports, and order history logs for your strategy.

⦁ Chapter 10, Algorithmic Trading – Paper Trading, explains how to paper trade your own algorithmic trading strategy in live markets using two strategy coding examples involving regular and bracket orders, respectively. You will also learn how to fetch execution logs and various types of paper trading reports, including profit and loss reports, statistics reports, and order history logs, in real time for your strategy.

⦁ Chapter 11, Algorithmic Trading – Real Trading, explains how to real trade your own algorithmic trading strategy in live markets and real money using two strategy coding examples involving regular and bracket orders, respectively. You will also learn how to fetch execution logs and various types of real trading reports, including profit and loss reports and statistics reports, in real time for your strategy.