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立即開始,按照自己的計劃學習。

第 2 門課程(共 3 門)

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中級

完成時間大約為11 小時

建議:23 hours/week...

英語(English)

字幕:英語(English)

您將獲得的技能

Algorithmic TradingPython ProgrammingMachine Learning

100% 在線

立即開始,按照自己的計劃學習。

第 2 門課程(共 3 門)

可靈活調整截止日期

根據您的日程表重置截止日期。

中級

完成時間大約為11 小時

建議:23 hours/week...

英語(English)

字幕:英語(English)

教學大綱 - 您將從這門課程中學到什麼

1

1

完成時間為 3 小時

Introduction to Quantitative Trading and TensorFlow

完成時間為 3 小時
10 個視頻 (總計 46 分鐘), 1 個閱讀材料, 2 個測驗
10 個視頻
Basic Trading Strategy Entries and Exits Endogenous Exogenous7分鐘
Basic Trading Strategy Building a Trading Model2分鐘
Advanced Concepts in Trading Strategies6分鐘
Introduction to TensorFlow1分鐘
Estimator API3分鐘
Predicting real estate house values using simple data set5分鐘
Estimator API Lab Introduction39
Getting Started with Google Cloud Platform and Qwiklabs3分鐘
Estimator API Lab Solution10分鐘
1 個閱讀材料
Welcome to Using Machine Learning in Trading and Finance10分鐘
1 個練習
Understand Quantitative Strategies
2

2

完成時間為 2 小時

Build a Pair Trading Strategy Prediction Model

完成時間為 2 小時
9 個視頻 (總計 56 分鐘), 2 個測驗
9 個視頻
Picking Pairs4分鐘
Picking Pairs with Clustering8分鐘
How to Implement a Pair Strategy9分鐘
Evaluate Results of a Pair Trade6分鐘
Backtesting and Avoiding Overfitting6分鐘
Next Steps: Improvements to Your Pairs Strategy5分鐘
Pairs Trading Lab Introduction30
Pairs Trading Lab Solution7分鐘
1 個練習
Pairs Trading Strategy and Backtesting
3

3

完成時間為 2 小時

Build a Momentum-based Trading System

完成時間為 2 小時
13 個視頻 (總計 77 分鐘), 1 個測驗
13 個視頻
Building a Momentum Trading Model7分鐘
Define the Problem9分鐘
Collect the Data2分鐘
Creating Features3分鐘
Split the Data3分鐘
Selecting a Machine Learning Algorithm3分鐘
Backtest on Unseen Data1分鐘
Understanding the Code: Simple ML Strategies to Generate Trading Signal9分鐘
Kalman Filter Introduction11分鐘
Kalman Filter Trading Applications6分鐘
Momentum Trading Lab Introduction43
Momentum Trading Lab Solution7分鐘

講師

授課教師 Jack Farmer 的圖片

Jack Farmer

Curriculum Director
New York Institute of Finance
授課教師 Ram Seshadri 的圖片

Ram Seshadri

Machine Learning Consultant
Google Cloud Platform

關於 New York Institute of Finance

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....

關於 Google 云端平台

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....

關於 Machine Learning for Trading 專項課程

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 long-term trading strategies, short-term trading strategies, and hedging strategies. 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 foundational knowledge of financial markets (equities, bonds, derivatives, market structure, hedging)....
Machine Learning for Trading

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