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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/machine-learning-trading-finance
课程评论：没有评论
课程名称：在交易和金融中使用机器学习 课程概述：本课程为使用机器学习技术开发高级交易策略奠定基础。您将学习每种交易策略的关键组成部分，无论其复杂程度如何。课程涵盖多种交易策略，包括量化交易、对冲交易和动量交易。到课程结束时，您将能够设计基本的量化交易策略，使用Keras和TensorFlow构建机器学习模型，建立对冲交易策略预测模型并进行回测，以及建立基于动量的交易模型并进行回测。 成功完成本课程的学习，您应具备高级Python编程能力，并熟悉与机器学习相关的库，例如Scikit-Learn、StatsModels和Pandas。建议有SQL的经验，同时需要具备统计学背景（包括期望值、标准差、高斯分布、高阶矩、概率、线性回归）和金融市场的基础知识（包括股票、债券、衍生品、市场结构、对冲）。 课程大纲： 1. 量化交易与TensorFlow介绍 - 讨论每种交易策略的关键组成部分，帮助您开发更高级的机器学习策略。 2. TensorFlow简介 3. 使用Tensorflow 2和Keras训练神经网络 4. 建立基于动量的交易系统 - 动量交易是根据近期价格趋势的强度进行资产买卖的策略。本模块将介绍价格动量的概念及其在金融市场中的应用。 5. 建立对冲交易策略预测模型 - 本模块将介绍对冲交易，包括其定义、盈利方法及选取合适交易对的注意事项。 通过本课程，您将能够掌握先进的交易策略，通过机器学习技术提升交易决策能力。
Name:Introduction to Quantitative Trading and TensorFlow
Description:In this module we discuss the key components that are common to every trading strategy, no matter how complex. This foundation will help guide you as you develop more advanced strategies using machine learning techniques.
Name:Introduction to TensorFlow
Description:
Name:Training neural networks with Tensorflow 2 and Keras
Description:
Name:Build a Momentum-based Trading System
Description:Momentum trading is a strategy in which traders buy or sell assets according to the strength of recent price trends. Price momentum is similar to momentum in physics, where mass multiplied by velocity determines the persistence with which an object will follow its current path (like a heavy train on a track). In financial markets, however, momentum is determined by other factors like trading volume and rate of price changes. Momentum traders bet that an asset price that is moving strongly in a given direction will continue to move in that direction until the trend loses strength or reverses. This module teaches you all about momentum trading.
Name:Build a Pair Trading Strategy Prediction Model
Description:In this module, we introduce pairs trading. We will discuss what pairs trading is, and how you can make money doing it. We will discuss what you need to know about the members to form a suitable pair.
This course provides the foundation for developing advanced trading strategies using machine learning techniques. In this course, you’ll review the key components that are common to every trading strategy, no matter how complex. You’ll be introduced to multiple trading strategies including quantitative trading, pairs trading, and momentum trading. By the end of the course, you will be able to design basic quantitative trading strategies, build machine learning models using Keras and TensorFlow, build a pair trading strategy prediction model and back test it, and build a momentum-based trading model and back test it. To be successful in this course, you should have advanced competency in Python programming and familiarity with pertinent libraries for machine learning, such as Scikit-Learn, StatsModels, and Pandas. Experience with SQL is recommended. You should have a background in statistics (expected values and standard deviation, Gaussian distributions, higher moments, probability, linear regressions) and foundational knowledge of financial markets (equities, bonds, derivatives, market structure, hedging).
