课程信息

36,309 次近期查看

100% 在线

立即开始,按照自己的计划学习。

第 2 门课程(共 3 门)

可灵活调整截止日期

根据您的日程表重置截止日期。

中级

完成时间大约为13 小时

建议:16 hours/week...

英语(English)

字幕:英语(English)

您将获得的技能

Algorithmic TradingPython ProgrammingMachine Learning

100% 在线

立即开始,按照自己的计划学习。

第 2 门课程(共 3 门)

可灵活调整截止日期

根据您的日程表重置截止日期。

中级

完成时间大约为13 小时

建议:16 hours/week...

英语(English)

字幕:英语(English)

教学大纲 - 您将从这门课程中学到什么

1

1

完成时间为 3 小时

Introduction to Quantitative Trading and TensorFlow

完成时间为 3 小时
10 个视频 (总计 46 分钟), 1 个阅读材料, 2 个测验
10 个视频
Basic Trading Strategy Entries and Exits Endogenous Exogenous7分钟
Basic Trading Strategy Building a Trading Model2分钟
Advanced Concepts in Trading Strategies6分钟
Introduction to TensorFlow1分钟
Estimator API3分钟
Predicting real estate house values using simple data set5分钟
Estimator API Lab Introduction39
Getting Started with Google Cloud Platform and Qwiklabs3分钟
Estimator API Lab Solution10分钟
1 个阅读材料
Welcome to Using Machine Learning in Trading and Finance10分钟
1 个练习
Understand Quantitative Strategies
2

2

完成时间为 2 小时

Build a Pair Trading Strategy Prediction Model

完成时间为 2 小时
9 个视频 (总计 56 分钟)
9 个视频
Picking Pairs4分钟
Picking Pairs with Clustering8分钟
How to Implement a Pair Strategy9分钟
Evaluate Results of a Pair Trade6分钟
Backtesting and Avoiding Overfitting6分钟
Next Steps: Improvements to Your Pairs Strategy5分钟
Pairs Trading Lab Introduction30
Pairs Trading Lab Solution7分钟
1 个练习
Pairs Trading Strategy and Backtesting
3

3

完成时间为 2 小时

Build a Momentum-based Trading System

完成时间为 2 小时
13 个视频 (总计 77 分钟)
13 个视频
Building a Momentum Trading Model7分钟
Define the Problem9分钟
Collect the Data2分钟
Creating Features3分钟
Split the Data3分钟
Selecting a Machine Learning Algorithm3分钟
Backtest on Unseen Data1分钟
Understanding the Code: Simple ML Strategies to Generate Trading Signal9分钟
Kalman Filter Introduction11分钟
Kalman Filter Trading Applications6分钟
Momentum Trading Lab Introduction43
Momentum Trading Lab Solution7分钟
3.8
29 条评论Chevron Right

来自Using Machine Learning in Trading and Finance的热门评论

创建者 PLFeb 29th 2020

The course is inspiring. It gave me another perspective of learning trading not just for Machine Learning also for day to day trading algorithm.

创建者 LTFeb 9th 2020

Very interesting course with integrated notebooks to learn concepts of how to apply machine learning to trading and finance

关于 ??????

The New York Institute of Finance (NYIF), is a global leader in training for financial services and related industries. Started by the New York Stock Exchange in 1922, it now trains 250,000+ professionals in over 120 countries. NYIF courses cover everything from investment banking, asset pricing, insurance and market structure to financial modeling, treasury operations, and accounting. The institute has a faculty of industry leaders and offers a range of program delivery options, including self-study, online courses, and in-person classes. Its US customers include the SEC, the Treasury, Morgan Stanley, Bank of America and most leading worldwide banks....

关于 Google ????

We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success....

关于 Machine Learning for Trading 专项课程

This Specialization is for finance professionals, including but not limited to hedge fund traders, analysts, day traders, those involved in investment management or portfolio management, and anyone interested in gaining greater knowledge of how to construct effective trading strategies using Machine Learning. Alternatively, this specialization can be for machine learning professionals who seek to apply their craft to quantitative trading strategies. The courses will teach you how to create various trading strategies using Python. By the end of the Specialization, you will be able to create quantitative trading strategies that you can train and implement. You will also learn how to use reinforcement learning strategies to create algorithms that can update and train themselves. To be successful in this Specialization, you should have a basic competency in Python programming and familiarity with pertinent libraries for machine learning, such as Scikit-Learn, StatsModels, and Pandas. Experience with SQL will be helpful. You should have a background in statistics (expected values and standard deviation, Gaussian distributions, higher moments, probability, linear regressions) and a basic knowledge of financial markets (equities, bonds, derivatives, market structure, hedging)....
Machine Learning for Trading

常见问题

  • ???????????????????????????????????????????????????????????????????????????????????????????

  • ?????????????????????????????????????????????????????????????????????????????????????????????????????????????

还有其他问题吗?请访问 学生帮助中心