Python Algorithmic Trading Cookbook: All the recipes you need to implement your own trading strategies in Python

Book Description

Implement investment strategies using real market data to perform effective financial and data analysis using Python

Key Features

• Use core Python libraries to devise investment strategies to carry out financial analysis tasks
• Implement necessary changes to your algorithmic strategies without human intervention
• Uncover common and not-so-common challenges faced in the algorithmic trading domain using varied financial data

Book Description

Python can be used to build and execute algorithmic trading strategies. This book could help you increase your chances of making profits in the stock market. It can help you automate trading to find the right strategy for making effective decisions that would otherwise be impossible for human traders.

After setting up the Python environment for trading, you’ll learn the important aspects of financial markets. As you progress through the book, you’ll understand how to fetch financial instruments, and query candle and historical data. The book also demonstrates how to compute and plot technical indicators, and create algorithmic trading strategies. Next, you’ll uncover challenges faced while devising powerful algorithmic trading strategies, before focusing on how to optimize and make changes to your existing strategies based on changing customer needs. Later, you’ll learn how to use various ARIMA models based on different challenging scenarios. The concluding chapters will take you through performing backtesting on your trading strategy, performing paper trade, and finally executing a real trade using the algorithmic strategies that you’ve created from scratch.

By the end of this book, you’ll have learned how to implement various Python libraries to conduct key tasks in the algorithmic finance ecosystem using a recipe-based approach.

What you will learn

• Use Python to query and understand the financial market
• Fetch a list of exchanges, segments, and financial products to interact with the real market
• Develop algorithmic trading strategies for financial data analysis
• Compute candles, historical data, and ARIMA models to forecast time series data
• Perform backtesting and paper trading on algorithmic trading strategies
• Implement real trading in the live hours of stock markets
• Develop and improve the performance of strategies to gain consistent returns

Who This Book Is For

If you are a financial analyst, financial trader, data analyst, or algorithmic trader who wants to learn algorithmic trading techniques to address challenges faced in the finance domain, then this book is for you. Basic knowledge of financial terminologies and working knowledge of the Python programming language are expected.

中文：

书名：Python算法交易手册：在Python中实现您自己的交易策略所需的所有食谱

使用真实市场数据实施投资策略，使用Python执行有效的财务和数据分析

主要特点

• 使用核心Python库设计投资策略以执行财务分析任务
• 在没有人工干预的情况下对算法策略进行必要的更改
• 使用各种金融数据揭示算法交易领域面临的常见和不太常见的挑战

图书描述

可以使用Python来构建和执行算法交易策略。这本书可以帮助你增加在股市获利的机会。它可以帮助你自动化交易，找到正确的策略，做出人类交易员不可能做出的有效决策。

在为交易设置了Python环境之后，您将学习金融市场的重要方面。在阅读本书的过程中，您将了解如何获取金融工具以及查询蜡烛和历史数据。这本书还演示了如何计算和绘制技术指标，并创建算法交易策略。接下来，你将发现在设计强大的算法交易策略时面临的挑战，然后专注于如何根据不断变化的客户需求优化和改变现有策略。稍后，您将学习如何根据不同的挑战场景使用各种ARIMA模型。最后一章将带你完成对你的交易策略进行回溯测试，进行纸上交易，最后使用你从头开始创建的算法策略执行一笔真正的交易。

到本书结束时，您将学会如何实现各种Python库，以使用基于配方的方法来执行算法金融生态系统中的关键任务。

What you will learn

• Use Python to query and understand the financial market
• 获取交易所、细分市场和金融产品的列表，以与真实市场互动
• Develop algorithmic trading strategies for financial data analysis
• 计算蜡烛、历史数据和ARIMA模型以预测时间序列数据
• Perform backtesting and paper trading on algorithmic trading strategies
• Implement real trading in the live hours of stock markets
• Develop and improve the performance of strategies to gain consistent returns

Who This Book Is For

如果你是一名金融分析师、金融交易员、数据分析师或算法交易员，想要学习算法交易技术来应对金融领域面临的挑战，那么这本书是为你而写的。要求具备金融术语的基本知识和Python编程语言的工作知识。