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所在平台: Udemy |
课程主页: https://www.udemy.com/course/python-trading-algo/
课程评论：没有评论
课程名称：使用Python进行算法交易：构建指标与风险管理 课程概述： 本课程旨在为想要学习创建自己的交易算法的交易者提供基础知识。学员将学习Python的基本语法，包括所有原生数据类型及控制流结构，确保能够在代码中实现决策逻辑。尽管交易具有挑战性，但它同样能带来丰厚的回报。通过Python，学员能够建立一个系统化的基于规则的算法，有效地实现交易目标。此外，Python也是适合使用多种机器学习技术进行AI算法的完美语言，相关的AI课程将在不久的将来推出。 本课程内容涵盖了构建算法交易所需的Python语法，学员将掌握如何使用Pandas处理日期时间对象和错误处理。接下来，将学习如何利用Python连接到MetaTrader5终端，从经纪商那里程序化获取市场数据和账户信息。课程还将教授如何构建适合个人交易风格的指标，可以通过Pandas、Ta-Lib或自定义函数实现。此外，学员还将学习如何计算头寸大小，决定止损位，查询账户信息以完成计算。课程将讲述如何使用Python与经纪商进行沟通，以执行与风险承受能力相符的交易，以及如何设置止损和获利水平、将止损移动到盈亏平衡点，以及如何在之后更新止损水平。 在掌握这些主题后，学员将能够根据自己的交易风格构建复杂的风险管理策略。最终，学员将对从零开始构建算法交易策略有清晰的认知，掌握创建个人算法策略所需的工具，并能够管理持仓，还能搭建回测环境，以系统性地构建和测试策略。本系列课程的目标是使学员理解构建算法交易策略的全过程，确保每位学员都掌握必要的工具与知识。
Are you a trader who is interested in learning how to build their own trading algorithm?If so, this course will teach you the basics of Python - you will learn about all the native data types in Python, and know how to work with control flow structure so that you can have decision logic built into your code.Trading is hard, but it is also highly rewarding. With Python, you can put in a methodical system to build your own rule-based algorithm in order to get to your goal efficiently.Python is also the perfect language for AI-based algorithms using a variety of machine learning techniques. The AI-based courses are coming soon.This complete course of algo trading with Python will teach all the Python syntax you need to know, and get you ready for working with Pandas, taking care of the DateTime objects, and handling errors. You will then immediately learn about how to use Python to connect to the MetaTrader5 terminal, and get market data as well as account information programmatically from your broker directly. You will also learn about constructing indicators that work for your style of trading, by using Pandas, Ta-Lib, or writing your own user-defined functions. You will learn how to programmatically compute position size but first decide where you would like to place your stop loss level, and then query some account information to complete the computation. You will learn about the specific ways that you will communicate, using Python, with your brokers to enter and/or exit trades with the computed size for your risk tolerance. Further, you will also learn about how to set the stop loss and take profit, how to move stop loss to breakeven, and how to update (trail) your stop-loss level after that point. Once you have learned all about these topics, you are able to build as many elaborate risk management strategies as you want in a way that you like to trade.At the end of this course, you will have a firm understanding of what goes into building an algorithmic trading strategy from scratch. You will have not only all the tools necessary to create your own algorithmic strategies, but you will also know how to manage your positions, as well as take what you already know and set up a backtesting environment for yourself, so that you are able to systematically build and test strategies on an on-going basis.The goal of the series is to give you an understanding of what goes into building an algorithmic trading strategy from scratch. By the end of the three-part series, you should have not only all the tools necessary to create your own algorithmic strategies, but you will also know how to manage your positions.
