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所在平台: Udemy |
课程主页: https://www.udemy.com/course/trading-bot-with-python/
课程评论：没有评论
课程名称：使用Python开发交易机器人 课程概述：您是否希望学习如何开发股票市场投资机器人？或者想要优化您的交易策略？在本课程中，我们将教您实现这些目标以及更多！我们将从零开始学习Python编程，并逐步提升我们的知识，直到能够完成以下任务：1）下载数据并根据我们的需求进行转换；2）开发和回测策略；3）开发交易机器人。本课程分为七个不同模块： 1. **课程介绍**：在这一部分，我们将探讨课程大纲，学习如何使用Google Colab以及开始课程所需的其他基本信息。 2. **Python基础**：我们将学习编程的基本元素，例如变量、类和函数。 3. **Pandas及其他有用的包**：我们将学习如何使用Pandas和其他工具下载和处理数据。 4. **Alpaca API的使用**：在此部分，我们将学习如何下载金融数据和下达买卖订单。 5. **金融指标**：我们将了解一些金融指标的理论基础及其计算方法。 6. **回测**：我们将使用金融数据优化策略参数，以尽可能多地赚取利润。 7. **创建交易机器人**：最后，我们将学习如何创建一个可以自主投资的交易机器人，无需我们持续监控。 通过本课程，您将掌握开发和优化股票交易机器人的技能，为您的投资之旅奠定良好基础。
Would you like to learn how to develop bots to invest in the stock market? Or would you like to optimize your strategies?In this course we will teach you how to fulfil these objectives and more! We are going to learn how to program in Python from scratch and build our knowledge until we are able to: 1) download data and transform it according to our wants and needs; 2) develop and backtest strategies; and 3) develop trading bots. This course is divided in 7 different modules:Introduction to the course. In this first section we are going to explore the outline of the course, how to use google colab and other basic pieces of information needed to start the course.Introduction to Python. Here we are going to learn the essential elements of programming like what are variables, classes and functions.Pandas and other useful packages. We will learn how to use pandas and other packages that will allow us to download and manipulate data. Use of Alpaca's API. Where we will learn to download financial data and place buy/sell orders.Financial indicators. Here we will learn the theory behind some financial indicators and how to calculate them.Backtesting. In this section we are going to use financial data to optimize the parameters of our strategies in order to earn as much money as we can. Creating a trading bot. Finally we are going to learn how to create a trading bot that will invest on its own without our constant supervision.
