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.
Ce cours fait partie de la Spécialisation Machine Learning for Trading
Reinforcement Learning for Trading Strategies
Offert par
New York Institute of Finance
Google Cloud
À propos de ce cours
29,304 consultations récentes
Ce que vous allez apprendre
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
Compétences que vous acquerrez
Reinforcement Learning Model DevelopmentReinforcement Learning Trading Algorithm OptimizationReinforcement Learning Trading Strategy DevelopmentReinforcement Learning Trading Algo Development
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 3 sur 3 dans le
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Niveau intermédiaire
Approx. 13 heures pour terminer
Recommandé : 19 hours/week
Anglais
Sous-titres : Anglais
Programme du cours : ce que vous apprendrez dans ce cours
3 heures pour terminer
Introduction to Course and Reinforcement Learning
In this module, reinforcement learning is introduced at a high level. The history and evolution of reinforcement learning is presented, including key concepts like value and policy iteration. Also, the benefits and examples of using reinforcement learning in trading strategies is described. We also introduce LSTM and AutoML as additional tools in your toolkit to use in implementing trading strategies.
3 heures pour terminer
10 vidéos (Total 64 min), 1 lecture, 1 quiz
10 vidéos
What is Reinforcement Learning?9 min
History Overview2 min
Value Iteration9 min
Policy Iteration6 min
TD Learning8 min
Q Learning6 min
Benefits of Reinforcement Learning in Your Trading Strategy6 min
DRL Advantages for Strategy Efficiency and Performance7 min
Introduction to Qwiklabs3 min
1 lecture
Idiosyncrasies and challenges of data driven learning in electronic trading10 min
5 heures pour terminer
Neural Network Based Reinforcement Learning
In the previous module, reinforcement learning was discussed before neural networks were introduced. In this module, we look at how reinforcement learning has been integrated with neural networks. We also look at LSTMs and how they can be applied to time series data.
5 heures pour terminer
9 vidéos (Total 39 min)
9 vidéos
TD-Gammon3 min
Deep Q Networks - Loss2 min
Deep Q Networks Memory2 min
Deep Q Networks - Code3 min
Policy Gradients4 min
Actor-Critic3 min
What is LSTM?7 min
More on LSTM4 min
Applying LSTM to Time Series Data7 min
4 heures pour terminer
Portfolio Optimization
In this module we discuss the practical steps required to create a reinforcement learning trading system. Also, we introduce AutoML, a powerful service on Google Cloud Platform for training machine learning models with minimal coding.
4 heures pour terminer
10 vidéos (Total 54 min)
10 vidéos
Steps Required to Develop a DRL Strategy7 min
Final Checks Before Going Live with Your Strategy5 min
Investment and Trading Risk Management4 min
Trading Strategy Risk Management4 min
Portfolio Risk Reduction4 min
Why AutoML?13 min
AutoML Vision2 min
AutoML NLP3 min
AutoML Tables7 min
Avis
3.8
Meilleurs avis pour REINFORCEMENT LEARNING FOR TRADING STRATEGIES
par SAMar 10, 2020
The course covers broad and important topics on using AI for trading, but one will need to dig more quite extensively on alternative sources to deepen one's understanding
par MSMar 5, 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.
par SFMar 14, 2020
Good course introducing concepts in RL. Wish course provided more examples of using RL in stock prediction.
par GSMar 6, 2020
Great introduction to some very interesting concepts. Lots of hands on examples, and plenty to learn
À propos de 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.
À propos de Google Cloud
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.
À propos du Spécialisation Machine Learning for Trading
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).
Foire Aux Questions
Quand aurai-je accès aux vidéos de cours et aux devoirs ?
Une fois que vous êtes inscrit(e) pour un Certificat, vous pouvez accéder à toutes les vidéos de cours, et à tous les quiz et exercices de programmation (le cas échéant). Vous pouvez soumettre des devoirs à examiner par vos pairs et en examiner vous-même uniquement après le début de votre session. Si vous préférez explorer le cours sans l'acheter, vous ne serez peut-être pas en mesure d'accéder à certains devoirs.
À quoi ai-je droit si je m'abonne à cette Spécialisation ?
Lorsque vous vous inscrivez au cours, vous bénéficiez d'un accès à tous les cours de la Spécialisation, et vous obtenez un Certificat lorsque vous avez réussi. Votre Certificat électronique est alors ajouté à votre page Accomplissements. À partir de cette page, vous pouvez imprimer votre Certificat ou l'ajouter à votre profil LinkedIn. Si vous souhaitez seulement lire et visualiser le contenu du cours, vous pouvez accéder gratuitement au cours en tant qu'auditeur libre.
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