About this Course
최근 조회 39,560

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

다음 전문 분야의 3개 강좌 중 2번째 강좌:

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

완료하는 데 약 9시간 필요

권장: 19 hours/week...

영어

자막: 영어

귀하가 습득할 기술

Algorithmic TradingPython ProgrammingMachine Learning

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

다음 전문 분야의 3개 강좌 중 2번째 강좌:

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

완료하는 데 약 9시간 필요

권장: 19 hours/week...

영어

자막: 영어

강의 계획 - 이 강좌에서 배울 내용

1
완료하는 데 3시간 필요

Introduction to Quantitative Trading and TensorFlow

10개 동영상 (총 46분), 1 reading, 2 quizzes
10개의 동영상
Basic Trading Strategy Entries and Exits Endogenous Exogenous7m
Basic Trading Strategy Building a Trading Model2m
Advanced Concepts in Trading Strategies6m
Introduction to TensorFlow1m
Estimator API3m
Predicting real estate house values using simple data set5m
Estimator API Lab Introduction39
Getting Started with Google Cloud Platform and Qwiklabs3m
Estimator API Lab Solution10m
1개의 읽기 자료
Welcome to Using Machine Learning in Trading and Finance10m
1개 연습문제
Understand Quantitative Strategies
2
완료하는 데 2시간 필요

Build a Pair Trading Strategy Prediction Model

9개 동영상 (총 56분), 2 quizzes
9개의 동영상
Picking Pairs4m
Picking Pairs with Clustering8m
How to Implement a Pair Strategy9m
Evaluate Results of a Pair Trade6m
Backtesting and Avoiding Overfitting6m
Next Steps: Improvements to Your Pairs Strategy5m
Pairs Trading Lab Introduction30
Pairs Trading Lab Solution7m
1개 연습문제
Pairs Trading Strategy and Backtesting
3
완료하는 데 2시간 필요

Build a Momentum-based Trading System

13개 동영상 (총 77분), 1 quiz
13개의 동영상
Building a Momentum Trading Model7m
Define the Problem9m
Collect the Data2m
Creating Features3m
Split the Data3m
Selecting a Machine Learning Algorithm3m
Backtest on Unseen Data1m
Understanding the Code: Simple ML Strategies to Generate Trading Signal9m
Kalman Filter Introduction11m
Kalman Filter Trading Applications6m
Momentum Trading Lab Introduction43
Momentum Trading Lab Solution7m

강사

Image of instructor, Jack Farmer

Jack Farmer

Curriculum Director
New York Institute of Finance
Image of instructor, Ram Seshadri

Ram Seshadri

Machine Learning Consultant
Google Cloud Platform

Google 클라우드 정보

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....

Google Cloud 정보

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....

Machine Learning for Trading 전문 분야 정보

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

자주 묻는 질문

  • 강좌에 등록하면 바로 모든 비디오, 테스트 및 프로그래밍 과제(해당하는 경우)에 접근할 수 있습니다. 상호 첨삭 과제는 이 세션이 시작된 경우에만 제출하고 검토할 수 있습니다. 강좌를 구매하지 않고 살펴보기만 하면 특정 과제에 접근하지 못할 수 있습니다.

  • 강좌를 등록하면 전문 분야의 모든 강좌에 접근할 수 있고 강좌를 완료하면 수료증을 취득할 수 있습니다. 전자 수료증이 성취도 페이지에 추가되며 해당 페이지에서 수료증을 인쇄하거나 LinkedIn 프로필에 수료증을 추가할 수 있습니다. 강좌 내용만 읽고 살펴보려면 해당 강좌를 무료로 청강할 수 있습니다.

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