Hands on trading python quantconnect par pik jiri (29 résultats)
Hands-on Ai Trading With Python, Quantconnect and Aws
Pik, Jiri; Chan, Ernest P.; Broad, Jared; Sun, Philip; Singh, Vivek
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Hardback or Cased Book. Etat : New. Hands-On AI Trading with Python, Quantconnect, and AWS. Book.
Hands-On AI Trading with Python, QuantConnect, and AWS
Pik, Jiri; Chan, Ernest P.; Broad, Jared; Sun, Philip; Singh, Vivek
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Vendeur : California Books, Miami, FL, Etats-UnisCalifornia Books
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EUR 42,21
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Hardcover. Etat : new. Hardcover. Master the art of AI-driven algorithmic trading strategies through hands-on examples, in-depth insights, and step-by-step guidance Hands-On AI Trading with Python, QuantConnect, and AWS explores real-world applications of AI technologies in algorithmic trading. It provides practical examples wit…h complete code, allowing readers to understand and expand their AI toolbelt. Unlike other books, this one focuses on designing actual trading strategies rather than setting up backtesting infrastructure. It utilizes QuantConnect, providing access to key market data from Algoseek and others. Examples are available on the book's GitHub repository, written in Python, and include performance tearsheets or research Jupyter notebooks. The book starts with an overview of financial trading and QuantConnect's platform, organized by AI technology used: Examples include constructing portfolios with regression models, predicting dividend yields, and safeguarding against market volatility using machine learning packages like SKLearn and MLFinLab.Use principal component analysis to reduce model features, identify pairs for trading, and run statistical arbitrage with packages like LightGBM.Predict market volatility regimes and allocate funds accordingly.Predict daily returns of tech stocks using classifiers.Forecast Forex pairs' future prices using Support Vector Machines and wavelets.Predict trading day momentum or reversion risk using TensorFlow and temporal CNNs.Apply large language models (LLMs) for stock research analysis, including prompt engineering and building RAG applications.Perform sentiment analysis on real-time news feeds and train time-series forecasting models for portfolio optimization.Better Hedging by Reinforcement Learning and AI: Implement reinforcement learning models for hedging options and derivatives with PyTorch.AI for Risk Management and Optimization: Use corrective AI and conditional portfolio optimization techniques for risk management and capital allocation. Written by domain experts, including Jiri Pik, Ernest Chan, Philip Sun, Vivek Singh, and Jared Broad, this book is essential for hedge fund professionals, traders, asset managers, and finance students. Integrate AI into your next algorithmic trading strategy with Hands-On AI Trading with Python, QuantConnect, and AWS. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-UniPBShop.store UK
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EUR 36,56
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HRD. Etat : New. New Book. Shipped from UK. Established seller since 2000.
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Hands-On AI Trading with Python, QuantConnect, and AWS
Jiri Pik, Ernest P. Chan, Vivek Singh, Jared Broad, Philip Sun
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Vendeur : Rarewaves USA, OSWEGO, IL, Etats-UnisRarewaves USA
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EUR 47,27
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Hardback. Etat : New. Master the art of AI-driven algorithmic trading strategies through hands-on examples, in-depth insights, and step-by-step guidance Hands-On AI Trading with Python, QuantConnect, and AWS explores real-world applications of AI technologies in algorithmic trading. It provides practical examples with complete c…ode, allowing readers to understand and expand their AI toolbelt. Unlike other books, this one focuses on designing actual trading strategies rather than setting up backtesting infrastructure. It utilizes QuantConnect, providing access to key market data from Algoseek and others. Examples are available on the book's GitHub repository, written in Python, and include performance tearsheets or research Jupyter notebooks. The book starts with an overview of financial trading and QuantConnect's platform, organized by AI technology used: Examples include constructing portfolios with regression models, predicting dividend yields, and safeguarding against market volatility using machine learning packages like SKLearn and MLFinLab.Use principal component analysis to reduce model features, identify pairs for trading, and run statistical arbitrage with packages like LightGBM.Predict market volatility regimes and allocate funds accordingly.Predict daily returns of tech stocks using classifiers.Forecast Forex pairs' future prices using Support Vector Machines and wavelets.Predict trading day momentum or reversion risk using TensorFlow and temporal CNNs.Apply large language models (LLMs) for stock research analysis, including prompt engineering and building RAG applications.Perform sentiment analysis on real-time news feeds and train time-series forecasting models for portfolio optimization.Better Hedging by Reinforcement Learning and AI: Implement reinforcement learning models for hedging options and derivatives with PyTorch.AI for Risk Management and Optimization: Use corrective AI and conditional portfolio optimization techniques for risk management and capital allocation. Written by domain experts, including Jiri Pik, Ernest Chan, Philip Sun, Vivek Singh, and Jared Broad, this book is essential for hedge fund professionals, traders, asset managers, and finance students. Integrate AI into your next algorithmic trading strategy with Hands-On AI Trading with Python, QuantConnect, and AWS.
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Hands-On AI Trading with Python, QuantConnect, and AWS
Jiri Pik, Ernest P. Chan, Vivek Singh, Jared Broad, Philip Sun
- Couverture rigide
Vendeur : Rarewaves.com USA, London, LONDO, Royaume-UniRarewaves.com USA
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EUR 47,34
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Hardback. Etat : New. Master the art of AI-driven algorithmic trading strategies through hands-on examples, in-depth insights, and step-by-step guidance Hands-On AI Trading with Python, QuantConnect, and AWS explores real-world applications of AI technologies in algorithmic trading. It provides practical examples with complete c…ode, allowing readers to understand and expand their AI toolbelt. Unlike other books, this one focuses on designing actual trading strategies rather than setting up backtesting infrastructure. It utilizes QuantConnect, providing access to key market data from Algoseek and others. Examples are available on the book's GitHub repository, written in Python, and include performance tearsheets or research Jupyter notebooks. The book starts with an overview of financial trading and QuantConnect's platform, organized by AI technology used: Examples include constructing portfolios with regression models, predicting dividend yields, and safeguarding against market volatility using machine learning packages like SKLearn and MLFinLab.Use principal component analysis to reduce model features, identify pairs for trading, and run statistical arbitrage with packages like LightGBM.Predict market volatility regimes and allocate funds accordingly.Predict daily returns of tech stocks using classifiers.Forecast Forex pairs' future prices using Support Vector Machines and wavelets.Predict trading day momentum or reversion risk using TensorFlow and temporal CNNs.Apply large language models (LLMs) for stock research analysis, including prompt engineering and building RAG applications.Perform sentiment analysis on real-time news feeds and train time-series forecasting models for portfolio optimization.Better Hedging by Reinforcement Learning and AI: Implement reinforcement learning models for hedging options and derivatives with PyTorch.AI for Risk Management and Optimization: Use corrective AI and conditional portfolio optimization techniques for risk management and capital allocation. Written by domain experts, including Jiri Pik, Ernest Chan, Philip Sun, Vivek Singh, and Jared Broad, this book is essential for hedge fund professionals, traders, asset managers, and finance students. Integrate AI into your next algorithmic trading strategy with Hands-On AI Trading with Python, QuantConnect, and AWS.
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Vendeur : Brook Bookstore On Demand, Napoli, NA, ItalieBrook Bookstore On Demand
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EUR 36,08
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Etat : new.
Hands-on Ai Trading With Python, Quantconnect and Aws
Pik, Jiri; Chan, Ernest P.; Broad, Jared; Sun, Philip; Singh, Vivek
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Vendeur : GreatBookPricesUK, Woodford Green, Royaume-UniGreatBookPricesUK
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Hands-On AI Trading with Python, QuantConnect, and AWS
Pik, Jiri; Chan, Ernest P.; Broad, Jared; Sun, Philip; Singh, Vivek
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Vendeur : Ria Christie Collections, Uxbridge, Royaume-UniRia Christie Collections
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EUR 41,60
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Hands-On AI Trading with Python, QuantConnect and AWS
Pik, Jiri Jiri Pik, Ernest P. Chan, Jared Broad, Philip Sun, Vivek Singh,
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Vendeur : Chiron Media, Wallingford, Royaume-UniChiron Media
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Vendeur : Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandeKennys Bookshop and Art Galleries Ltd.
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Etat : as new. Wie neu/Like new.
Hands-on Ai Trading With Python, Quantconnect and Aws
Pik, Jiri; Chan, Ernest P.; Broad, Jared; Sun, Philip; Singh, Vivek
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Vendeur : Books Puddle, New York, NY, Etats-UnisBooks Puddle
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EUR 60,59
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Etat : New. 1st edition NO-PA16APR2015-KAP.
Hands-on Ai Trading With Python, Quantconnect and Aws
Pik, Jiri; Chan, Ernest P.; Broad, Jared; Sun, Philip; Singh, Vivek
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Vendeur : GreatBookPrices, Columbia, MD, Etats-UnisGreatBookPrices
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Etat : As New. Unread book in perfect condition.
Hands-on Ai Trading With Python, Quantconnect and Aws
Pik, Jiri; Chan, Ernest P.; Broad, Jared; Sun, Philip; Singh, Vivek
- Couverture rigide
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-UniGreatBookPricesUK
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Vendeur : Revaluation Books, Exeter, Royaume-UniRevaluation Books
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Vendeur : Russell Books, Victoria, BC, CanadaRussell Books
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Vendeur : Kennys Bookstore, Olney, MD, Etats-UnisKennys Bookstore
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Etat : New. 2025. 1st Edition. hardcover. . . . . . Books ship from the US and Ireland.
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Vendeur : Revaluation Books, Exeter, Royaume-UniRevaluation Books
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Hardcover. Etat : new. Hardcover. Master the art of AI-driven algorithmic trading strategies through hands-on examples, in-depth insights, and step-by-step guidance Hands-On AI Trading with Python, QuantConnect, and AWS explores real-world applications of AI technologies in algorithmic trading. It provides practical examples wit…h complete code, allowing readers to understand and expand their AI toolbelt. Unlike other books, this one focuses on designing actual trading strategies rather than setting up backtesting infrastructure. It utilizes QuantConnect, providing access to key market data from Algoseek and others. Examples are available on the book's GitHub repository, written in Python, and include performance tearsheets or research Jupyter notebooks. The book starts with an overview of financial trading and QuantConnect's platform, organized by AI technology used: Examples include constructing portfolios with regression models, predicting dividend yields, and safeguarding against market volatility using machine learning packages like SKLearn and MLFinLab.Use principal component analysis to reduce model features, identify pairs for trading, and run statistical arbitrage with packages like LightGBM.Predict market volatility regimes and allocate funds accordingly.Predict daily returns of tech stocks using classifiers.Forecast Forex pairs' future prices using Support Vector Machines and wavelets.Predict trading day momentum or reversion risk using TensorFlow and temporal CNNs.Apply large language models (LLMs) for stock research analysis, including prompt engineering and building RAG applications.Perform sentiment analysis on real-time news feeds and train time-series forecasting models for portfolio optimization.Better Hedging by Reinforcement Learning and AI: Implement reinforcement learning models for hedging options and derivatives with PyTorch.AI for Risk Management and Optimization: Use corrective AI and conditional portfolio optimization techniques for risk management and capital allocation. Written by domain experts, including Jiri Pik, Ernest Chan, Philip Sun, Vivek Singh, and Jared Broad, this book is essential for hedge fund professionals, traders, asset managers, and finance students. Integrate AI into your next algorithmic trading strategy with Hands-On AI Trading with Python, QuantConnect, and AWS. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Hands-On AI Trading with Python, QuantConnect, and AWS
Pik, Jiri; Chan, Ernest P.; Broad, Jared; Sun, Philip; Singh, Vivek
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Vendeur : Ubiquity Trade, Miami, FL, Etats-UnisUbiquity Trade
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EUR 78,69
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EUR 36,57
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Etat : NEW.
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Hands-On AI Trading with Python, QuantConnect, and AWS
Jiri Pik, Ernest P. Chan, Vivek Singh, Jared Broad, Philip Sun
- Couverture rigide
Vendeur : Rarewaves USA United, OSWEGO, IL, Etats-UnisRarewaves USA United
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EUR 49,17
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Hardback. Etat : New. Master the art of AI-driven algorithmic trading strategies through hands-on examples, in-depth insights, and step-by-step guidance Hands-On AI Trading with Python, QuantConnect, and AWS explores real-world applications of AI technologies in algorithmic trading. It provides practical examples with complete c…ode, allowing readers to understand and expand their AI toolbelt. Unlike other books, this one focuses on designing actual trading strategies rather than setting up backtesting infrastructure. It utilizes QuantConnect, providing access to key market data from Algoseek and others. Examples are available on the book's GitHub repository, written in Python, and include performance tearsheets or research Jupyter notebooks. The book starts with an overview of financial trading and QuantConnect's platform, organized by AI technology used: Examples include constructing portfolios with regression models, predicting dividend yields, and safeguarding against market volatility using machine learning packages like SKLearn and MLFinLab.Use principal component analysis to reduce model features, identify pairs for trading, and run statistical arbitrage with packages like LightGBM.Predict market volatility regimes and allocate funds accordingly.Predict daily returns of tech stocks using classifiers.Forecast Forex pairs' future prices using Support Vector Machines and wavelets.Predict trading day momentum or reversion risk using TensorFlow and temporal CNNs.Apply large language models (LLMs) for stock research analysis, including prompt engineering and building RAG applications.Perform sentiment analysis on real-time news feeds and train time-series forecasting models for portfolio optimization.Better Hedging by Reinforcement Learning and AI: Implement reinforcement learning models for hedging options and derivatives with PyTorch.AI for Risk Management and Optimization: Use corrective AI and conditional portfolio optimization techniques for risk management and capital allocation. Written by domain experts, including Jiri Pik, Ernest Chan, Philip Sun, Vivek Singh, and Jared Broad, this book is essential for hedge fund professionals, traders, asset managers, and finance students. Integrate AI into your next algorithmic trading strategy with Hands-On AI Trading with Python, QuantConnect, and AWS.
- Couverture rigide
Vendeur : AussieBookSeller, Truganina, VIC, AustralieAussieBookSeller
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 61,28
EUR 32,27 expéditionExpédition depuis Australie vers Etats-UnisQuantité disponible : 1 disponible(s)
Hardcover. Etat : new. Hardcover. Master the art of AI-driven algorithmic trading strategies through hands-on examples, in-depth insights, and step-by-step guidance Hands-On AI Trading with Python, QuantConnect, and AWS explores real-world applications of AI technologies in algorithmic trading. It provides practical examples wit…h complete code, allowing readers to understand and expand their AI toolbelt. Unlike other books, this one focuses on designing actual trading strategies rather than setting up backtesting infrastructure. It utilizes QuantConnect, providing access to key market data from Algoseek and others. Examples are available on the book's GitHub repository, written in Python, and include performance tearsheets or research Jupyter notebooks. The book starts with an overview of financial trading and QuantConnect's platform, organized by AI technology used: Examples include constructing portfolios with regression models, predicting dividend yields, and safeguarding against market volatility using machine learning packages like SKLearn and MLFinLab.Use principal component analysis to reduce model features, identify pairs for trading, and run statistical arbitrage with packages like LightGBM.Predict market volatility regimes and allocate funds accordingly.Predict daily returns of tech stocks using classifiers.Forecast Forex pairs' future prices using Support Vector Machines and wavelets.Predict trading day momentum or reversion risk using TensorFlow and temporal CNNs.Apply large language models (LLMs) for stock research analysis, including prompt engineering and building RAG applications.Perform sentiment analysis on real-time news feeds and train time-series forecasting models for portfolio optimization.Better Hedging by Reinforcement Learning and AI: Implement reinforcement learning models for hedging options and derivatives with PyTorch.AI for Risk Management and Optimization: Use corrective AI and conditional portfolio optimization techniques for risk management and capital allocation. Written by domain experts, including Jiri Pik, Ernest Chan, Philip Sun, Vivek Singh, and Jared Broad, this book is essential for hedge fund professionals, traders, asset managers, and finance students. Integrate AI into your next algorithmic trading strategy with Hands-On AI Trading with Python, QuantConnect, and AWS. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Hands-On AI Trading with Python, QuantConnect, and AWS
Jiri Pik, Ernest P. Chan, Vivek Singh, Jared Broad, Philip Sun
- Couverture rigide
Vendeur : Rarewaves.com UK, London, Royaume-UniRarewaves.com UK
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 43,64
EUR 75,77 expéditionExpédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : Plus de 20 disponibles
Hardback. Etat : New. Master the art of AI-driven algorithmic trading strategies through hands-on examples, in-depth insights, and step-by-step guidance Hands-On AI Trading with Python, QuantConnect, and AWS explores real-world applications of AI technologies in algorithmic trading. It provides practical examples with complete c…ode, allowing readers to understand and expand their AI toolbelt. Unlike other books, this one focuses on designing actual trading strategies rather than setting up backtesting infrastructure. It utilizes QuantConnect, providing access to key market data from Algoseek and others. Examples are available on the book's GitHub repository, written in Python, and include performance tearsheets or research Jupyter notebooks. The book starts with an overview of financial trading and QuantConnect's platform, organized by AI technology used: Examples include constructing portfolios with regression models, predicting dividend yields, and safeguarding against market volatility using machine learning packages like SKLearn and MLFinLab.Use principal component analysis to reduce model features, identify pairs for trading, and run statistical arbitrage with packages like LightGBM.Predict market volatility regimes and allocate funds accordingly.Predict daily returns of tech stocks using classifiers.Forecast Forex pairs' future prices using Support Vector Machines and wavelets.Predict trading day momentum or reversion risk using TensorFlow and temporal CNNs.Apply large language models (LLMs) for stock research analysis, including prompt engineering and building RAG applications.Perform sentiment analysis on real-time news feeds and train time-series forecasting models for portfolio optimization.Better Hedging by Reinforcement Learning and AI: Implement reinforcement learning models for hedging options and derivatives with PyTorch.AI for Risk Management and Optimization: Use corrective AI and conditional portfolio optimization techniques for risk management and capital allocation. Written by domain experts, including Jiri Pik, Ernest Chan, Philip Sun, Vivek Singh, and Jared Broad, this book is essential for hedge fund professionals, traders, asset managers, and finance students. Integrate AI into your next algorithmic trading strategy with Hands-On AI Trading with Python, QuantConnect, and AWS.
