About this Course

최근 조회 29,514

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

다음 전문 분야의 3개 강좌 중 3번째 강좌:

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

완료하는 데 약 13시간 필요

권장: 19 hours/week...

영어

자막: 영어

배울 내용

  • Understand the the structure and techniques used in reinforcement learning (RL) strategies

  • Describe the steps required to develop and test an RL trading strategy

  • Describe the methods used to optimize an RL trading strategy

귀하가 습득할 기술

Reinforcement Learning Model DevelopmentReinforcement Learning Trading Algorithm OptimizationReinforcement Learning Trading Strategy DevelopmentReinforcement Learning Trading Algo Development

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

다음 전문 분야의 3개 강좌 중 3번째 강좌:

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

완료하는 데 약 13시간 필요

권장: 19 hours/week...

영어

자막: 영어

강의 계획 - 이 강좌에서 배울 내용

1

1

완료하는 데 3시간 필요

Introduction to Course and Reinforcement Learning

완료하는 데 3시간 필요
10개 동영상 (총 64분), 1 reading, 1 quiz
10개의 동영상
What is Reinforcement Learning?9m
History Overview2m
Value Iteration9m
Policy Iteration6m
TD Learning8m
Q Learning6m
Benefits of Reinforcement Learning in Your Trading Strategy6m
DRL Advantages for Strategy Efficiency and Performance7m
Introduction to Qwiklabs3m
1개의 읽기 자료
Idiosyncrasies and challenges of data driven learning in electronic trading10m
2

2

완료하는 데 5시간 필요

Neural Network Based Reinforcement Learning

완료하는 데 5시간 필요
9개 동영상 (총 39분)
9개의 동영상
Deep Q Networks - Loss2m
Deep Q Networks Memory2m
Deep Q Networks - Code3m
Policy Gradients4m
Actor-Critic3m
What is LSTM?7m
More on LSTM4m
Applying LSTM to Time Series Data7m
3

3

완료하는 데 4시간 필요

Portfolio Optimization

완료하는 데 4시간 필요
10개 동영상 (총 54분)
10개의 동영상
Steps Required to Develop a DRL Strategy7m
Final Checks Before Going Live with Your Strategy5m
Investment and Trading Risk Management4m
Trading Strategy Risk Management4m
Portfolio Risk Reduction4m
Why AutoML?13m
AutoML Vision2m
AutoML NLP3m
AutoML Tables7m
3.8
10개의 리뷰Chevron Right

Reinforcement Learning for Trading Strategies의 최상위 리뷰

대학: MSMar 6th 2020

It was easy to follow but not easy. I learned a lot and I now have the confidence to implement Reinforcement learning to my own FX trading strategies. Thank you so much.

대학: GSMar 7th 2020

Great introduction to some very interesting concepts. Lots of hands on examples, and plenty to learn

New York Institute of Finance 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 클라우드 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 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

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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