Using Machine Learning in Trading and Finance

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课程主页: https://www.coursera.org/archive/machine-learning-trading-finance

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课程大纲

Introduction to Quantitative Trading and TensorFlow
Build a Pair Trading Strategy Prediction Model
Build a Momentum-based Trading System

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This course is for finance professionals, investment management professionals, and traders. Alternatively, this Specialization can be for machine learning professionals who seek to apply their craft to trading strategies. At the end of the course you will be able to do the following: - Design basic quantitative trading strategies - Use Keras and Tensorflow to build machine learning models - Build a pair trading strategy prediction model and back test it - Build a momentum-based trading model and back test it To be successful in this course, you should have a basic competency in Python programming and familiarity with the Scikit Learn, Statsmodels and Pandas library. 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).

在贸易和金融中使用机器学习:本课程面向金融专业人士,投资管理专业人士和交易员。或者,该专业化课程可用于寻求将自己的手艺应用于交易策略的机器学习专业人员。 在课程结束时,您将可以执行以下操作: -设计基本的定量交易策略 -使用Keras和Tensorflow建立机器学习模型 -建立配对交易策略预测模型并对其进行回测 -建立基于动量的交易模型并对其进行回测 为了成功完成本课程,您应该具备Python编程的基本能力,并且熟悉Scikit Learn,Statsmodels和Pandas库。您应该具有统计学背景(期望值和标准偏差,高斯分布,高阶矩,概率,线性回归),以及金融市场的基础知识(股票,债券,衍生产品,市场结构,对冲)。

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