quanxiel/course/01-introduction.md

01 · Introduction（课程总览）

• 系列：Full Algorithmic Trading Using Python
• 频道：TradeOptionsWithMe ｜ 本集：Introduction（课程总览）
• 时长：7 分 19 秒 ｜ 原视频：https://youtu.be/EeSrQdab0s0
• 本地视频：videos/01-introduction.mp4

🎯 本集要点（中文导读）

• 系列目标：把算法交易的完整开发流程讲清楚——从想法生成 → 代码实现 → 回测优化 → 实盘部署。
• 技术栈：Python + QuantConnect 平台（网页自带 IDE，无需本地装软件，跟着敲代码即可）。
• 数据：QuantConnect 免费提供大量数据（美股/期权等，分钟级），支持导入自定义数据，省去自己抓数据的耗时与不稳定。
• 代码隐私：不主动公开则平台尊重算法 IP；不放心也可本地部署其开源引擎（Lean）。
• 库支持：内置数百个常用 Python 库（TensorFlow、NLTK 等），import 即用。
• 前置要求：Python 基础（变量/条件/循环/函数/列表·字典·集合/类）+ 基础交易概念（股票、做多/做空）；无需算法交易经验。本系列会用到 pandas / numpy / matplotlib。
• 账户：免费账户足够学习与回测；实盘需付费 live trading 节点。
• 学习建议：边看边动手，多改参数、多做小实验，效果远好于被动观看。

📝 完整文稿（英文 · 自动转写）

由本地 ASR（faster-whisper）从视频音轨转录，未人工校对，供检索/精读使用。原始讲解以上方视频为准。

Hello and welcome back to the first video of a brand new video series. Over the past few months I've gotten countless requests to create a hands-on video course on algorithmic trading and that's exactly what this series is going to be. The purpose of this introductory video is to outline what you can expect to learn, the prerequisites for this course and which resources we will be using. That said, let's cut right to the chase and start by going over what you will learn in this video series. My first goal with this series is to bring the entire trading algorithm development process closer to you. We will cover everything from idea generation, code implementation, testing and optimizing to the actual live deployment of your algorithms. For this we will be using Python and the QuantConnect algorithmic trading platform. The QuantConnect platform has its own integrated development environment which allows you to create your algorithms right on their website. So this means that you won't have to install any additional software for you to be able to follow along. In this course we will cover all the major aspects of the QuantConnect API so that you can code your own algorithms on your own after watching this video series. To accomplish this there will be numerous example algorithms so that you can gain the best possible insights into what an actual trading algorithm looks like. We will go over everything from very basic beginner algorithms to advanced machine learning algorithms. I will of course make all of the code from these example bots available by linking to it in the description box of each video. My goal is to create at least one example algorithm for every asset class that QuantConnect supports. That means no matter if you want to create trading bots for stocks, bonds, forex, crypto, CFDs, options or futures this course and QuantConnect has you covered. But note that in the beginning we will focus on equities since I find this the best way to get started. But don't worry the concepts learned for stock trading bots are just as important for forex, crypto or any other kind of trading bot. When it comes to developing and testing your trading algorithms one of the biggest problems is getting the right data. One solution for this would be to scrape data from different websites. The problem with this is that it can be very time consuming and unreliable. Besides that you usually won't be able to find all the data you need easily accessible for free. Luckily QuantConnect allows you to use the data of a bunch of different data vendors for free. They have a huge collection of data at a resolution as low as a minute for all US stocks, options and other assets. Furthermore they have already announced that they have plans to add data for other international markets as well. It is also possible to import your own custom data which we will also cover in one of the lessons. Besides data another big concern of algorithmic trading developers is for them to keep the intellectual property and privacy of their algorithms. As long as you don't personally share your algorithms QuantConnect does respect your code's IP and privacy. If however you don't trust them it is also possible to set up their open source trading engine for local development. But since this series is mostly aimed at beginners we will just be using the website for the coding. For more advanced trading algorithms it can be very useful to use some of Python's libraries such as TensorFlow for machine learning, NLTK for sentiment analysis or some other library. QuantConnect supports hundreds of Python's most popular libraries and since we will be using QuantConnect's development environment you won't have to manually install any of these. Instead we can just import them with a simple import statement. As you hopefully can see QuantConnect is a very flexible platform that pretty much allows you to create whatever algorithm you want to. This flexibility also means that their API can be a little overwhelming to learn. But don't worry we will cover all of the major aspects of QuantConnect's API in this course on a step-by-step basis. To accomplish this this video series will have both theory and application oriented videos. For the coding part of this series I highly recommend coding along and trying out minor deviations, adjustments and experiments on your own. This will yield a much better learning experience than just passively watching these videos. For you to be able to code along make sure to create a free QuantConnect account. There's a link in the description box below. QuantConnect offers both free and premium accounts. For all the coding and bag testing you won't need a premium account so I will try to mainly focus on the features that can be used without paying. But note that if you want to live trade an algorithm you will have to pay for a live trading server node on QuantConnect since your algorithm has to be able to receive data and communicate with your broker on an ongoing basis. Besides that a premium account can decrease bag test times and give you more available memory for your algorithms. But like I said you can also follow along and use QuantConnect with a completely free account. Last but not least let me quickly present some prerequisites for this course. Here I firstly want to say that this course is aimed at beginners so I don't expect you to have any algorithmic trading experience for you to be able to gain value from this course. That said besides a free QuantConnect account it would be very useful to already have some Python experience. I will not be covering Python basics in this course. If you're new to programming I highly recommend first learning some basic programming principles and Python syntax. As a good Python foundation I'd recommend to be familiar with things such as variables, conditionals, control flow, loops, functions and basic data structures such as lists, sets and dictionaries. Besides that it could also be useful to have some experience with basic object oriented programming. If you have never heard of the concept of a class it would be a good idea to quickly freshen up that knowledge. That said it is totally okay if you aren't an expert programmer or only have very difficult coding experience. I will do my best to explain everything as simple as possible. Besides that we will also be using a few modules such as pandas, numpy and matplotlib among others. But if you aren't an expert at these don't worry. If the demand is high enough I could also create an introductory video series on these modules and more basic Python data analysis topics at some point in the future. So if that's something you want to see definitely let me know in the comment section below. Besides Python QuantConnect also supports C-sharp but since the majority of the community uses Python that's what I will focus on in this course. Next to these programming prerequisites it would also be very useful to have some prior knowledge of basic trading and finance topics. You don't need any real-world trading experience but it would be great if you know what a stock is, what going long and short is and generally have a basic understanding of the markets. If you don't you can check out some of the other videos on my channel and the articles on tradeoptionswithme.com. With that being said I hope you are as excited as I am to get started with this algorithmic trading series. In the next video we will get started with the course content by looking at the algorithm development process and how trading algorithms work. Thanks for watching and see you in the next video.