Langue: anglais
Edité par O'Reilly Media (edition 1), 2024
ISBN 10 : 1098148398 ISBN 13 : 9781098148393
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Langue: anglais
Edité par O'Reilly Media 2/13/2024, 2024
ISBN 10 : 1098148398 ISBN 13 : 9781098148393
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Ajouter au panierPaperback or Softback. Etat : New. Deep Learning for Finance: Creating Machine & Deep Learning Models for Trading in Python. Book.
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Ajouter au panierEtat : New. Brand New! Not Overstocks or Low Quality Book Club Editions! Direct From the Publisher! We're not a giant, faceless warehouse organization! We're a small town bookstore that loves books and loves it's customers! Buy from Lakeside Books!
Langue: anglais
Edité par O'Reilly Media, Sebastopol, 2024
ISBN 10 : 1098148398 ISBN 13 : 9781098148393
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Ajouter au panierPaperback. Etat : new. Paperback. Deep learning is rapidly gaining momentum in the world of finance and trading. But for many professional traders, this sophisticated field has a reputation for being complex and difficult. This hands-on guide teaches you how to develop a deep learning trading model from scratch using Python, and it also helps you create and backtest trading algorithms based on machine learning and reinforcement learning. Sofien Kaabar--financial author, trading consultant, and institutional market strategist--introduces deep learning strategies that combine technical and quantitative analyses. By fusing deep learning concepts with technical analysis, this unique book presents outside-the-box ideas in the world of financial trading. This A-Z guide also includes a full introduction to technical analysis, evaluating machine learning algorithms, and algorithm optimization. Understand and create machine learning and deep learning models Explore the details behind reinforcement learning and see how it's used in time series Understand how to interpret performance evaluation metrics Examine technical analysis and learn how it works in financial markets Create technical indicators in Python and combine them with ML models for optimization Evaluate the models' profitability and predictability to understand their limitations and potential This hands-on guide teaches you how to develop a deep learning trading model from scratch using Python, and it also helps you create, trade, and back-test trading algorithms based on machine learning and reinforcement learning. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Ajouter au panierPaperback. Etat : New. Candlesticks have become a key component of platforms and charting programs for financial trading. With these charts, traders can learn underlying patterns for interpreting price action history and forecasts. This A-Z guide shows portfolio managers, quants, strategists, and analysts how to use Python to recognize, scan, trade, and backtest the profitability of candlestick patterns. Financial author, trading consultant, and institutional market strategist Sofien Kaabar shows you how to create a candlestick scanner and indicator so you can compare the profitability of these patterns. With this hands-on guide, you'll also explore a new type of charting system similar to candlesticks, as well as new patterns that have never been presented before. With this book, you will: Create and understand the conditions required for classic and modern candlestick patterns Learn the market psychology behind them Use a framework to learn how backtesting trading strategies are conducted Explore different charting systems and understand their limitations Import OHLC historical FX data in Python in different time frames Use algorithms to scan for and reproduce patterns Learn a pattern's potential by evaluating its profitability and predictability.
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Langue: anglais
Edité par O'Reilly Media, Sebastopol, 2022
ISBN 10 : 1098120477 ISBN 13 : 9781098120474
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
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Ajouter au panierPaperback. Etat : new. Paperback. Candlesticks have become a key component of platforms and charting programs for financial trading. With these charts, traders can learn underlying patterns for interpreting price action history and forecasts. This A-Z guide shows portfolio managers, quants, strategists, and analysts how to use Python to recognize, scan, trade, and backtest the profitability of candlestick patterns. Financial author, trading consultant, and institutional market strategist Sofien Kaabar shows you how to create a candlestick scanner and indicator so you can compare the profitability of these patterns. With this hands-on guide, you'll also explore a new type of charting system similar to candlesticks, as well as new patterns that have never been presented before. With this book, you will: Create and understand the conditions required for classic and modern candlestick patterns Learn the market psychology behind them Use a framework to learn how backtesting trading strategies are conducted Explore different charting systems and understand their limitations Import OHLC historical FX data in Python in different time frames Use algorithms to scan for and reproduce patterns Learn a pattern's potential by evaluating its profitability and predictability Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Ajouter au panierPaperback. Etat : New. Deep learning is rapidly gaining momentum in the world of finance and trading. But for many professional traders, this sophisticated field has a reputation for being complex and difficult. This hands-on guide teaches you how to develop a deep learning trading model from scratch using Python, and it also helps you create and backtest trading algorithms based on machine learning and reinforcement learning.Sofien Kaabar-financial author, trading consultant, and institutional market strategist-introduces deep learning strategies that combine technical and quantitative analyses. By fusing deep learning concepts with technical analysis, this unique book presents outside-the-box ideas in the world of financial trading. This A-Z guide also includes a full introduction to technical analysis, evaluating machine learning algorithms, and algorithm optimization.Understand and create machine learning and deep learning modelsExplore the details behind reinforcement learning and see how it's used in time seriesUnderstand how to interpret performance evaluation metricsExamine technical analysis and learn how it works in financial marketsCreate technical indicators in Python and combine them with ML models for optimizationEvaluate the models' profitability and predictability to understand their limitations and potential.
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
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Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
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