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所在平台: Udemy |
课程主页: https://www.udemy.com/course/complete-algorthmic-forex-trading-and-back-testing-system/
课程评论：没有评论
课程名称：完整算法外汇交易与回测系统 课程概述：外汇交易虽然有趣，但并不简单！要在当今市场上取得成功，您必须具备测试策略、自动化交易和获取信息的能力。重要提示：本课程将使用Oanda API服务，在大多数国家可用，但请在购买前确认可用性。欧盟地区不适用。无论是作为业余爱好还是职业发展，本课程将为您提供基础，帮助您： - 构建一个实时交易机器人 - 创建快速、准确的策略测试系统 - 从网络获取最新的头条、情绪、技术指标等信息 - 使用数据库存储和关联市场波动的数据 - 构建一个展示最新价格、情绪和其他市场数据的网页应用 我们将从学习如何使用Python访问Oanda REST API开始。接着，下载几千根蜡烛图并开发一个简单的策略回测，测试多个参数和货币对。我们将利用回测结果学习如何将结果自动导出为带有表格和图形的电子表格格式。 在简单策略测试完成后，我们将获取更多数据——六年的多个时间框架数据。再次运行简单策略后，我们将转向实现蜡烛图模式检测和指标计算，同时使用多进程来加速测试。 接下来，我们将创建一个更全面的回测系统——包括点差和将蜡烛图细分为更短的时间框架。我们将选择两个在YouTube上拥有超过一百万次观看的视频中的策略进行测试，并评估其是否真的能够提供声称的90%胜率。 然后是激动人心的时刻——开发实时交易机器人。我们将开发一个稳健的交易机器人，能够交易多个货币对，并具备全面的日志记录功能。代码结构将便于策略的切换。 接下来，我们将学习如何使用多线程和事件、工作队列在实时流价格中作出响应并做出决策。我们还将学习如何使用Python的网页抓取技术获取实时情绪、技术指标、头条新闻和经济数据，同时创建MongoDB数据库来存储我们的数据。 最后，我们将使用著名的React框架开发一个网页应用，访问实时价格和情绪数据等信息。最终，我们将把交易机器人部署到云服务上。 本课程还包括Python以及HTML/CSS/JavaScript的快速入门附录。
Whilst fun, Forex trading is not easy! To be successful today, you must have the ability to test strategies, automate trading and access information.IMPORTANT:Note: For this course, we will use the Oanda API service. It is available in most countries worldwide, however please check before purchasing the course. You can check in video #3 called "Oanda account setup and API access". If you are in the EU, it's not available.Whether it's as a hobby or professional, this course will give you the foundation upon which you will be able to:Build a live trading botCreate a fast, accurate strategy testing systemRetrieve live headlines, sentiments, technicals and more from the web.Use databases to store and correlate data with market movesBuild a web application showing the latest prices, sentiments and other market dataLearn full stack development, using MongoDB, Python and JavaScript (with React)We will start by learning to use Python to access the Oanda REST API. Next, we'll download a few thousand candles and develop a simple strategy back test, testing multiple parameters and currency pairs at once. We'll use the results from this back test to learn how to automate the export of results into a spreadsheet format with tables and graphs.Once the simple strategy has been tested, we'll get hold of a lot more data - six years' worth for multiple time frames. We'll rerun our simple strategy, and then move on to implementing candle pattern detection and indicator calculation. We will also look at using multi-processing to speed up the testing even more.Now we have some more knowledge, it's time to create a more comprehensive back testing system - with spread and breaking candles down into finer time frames. For testing we will choose two strategies with over a million views on YouTube and assess whether they really give the claimed 90% win rate.It's now time to move on to the big moment - the live trading bot. We will develop a robust trading bot that trades multiple pairs with comprehensive logging. We will structure the code such that it is easy to swap in and out strategies.Now it's time to get more advanced and learn how stream prices live - using multi-threading with events and work queues to react to prices and make decisionsWe will learn how to use Web Scraping with Python to access live sentiments, technicals, headlines and economic data. Alongside this, we'll create a MongoDB database to store our data.Next up: React! We will use the famous framework to develop ourselves a web application that can access live prices, our sentiment data and much more.Finally, we will deploy our trading bot on a cloud service.The course includes a quick-start appendix for Python and for HTML/CSS/JavaScript.
