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Deep Learning Tools for Predicting Stock Market Movements

Om Deep Learning Tools for Predicting Stock Market Movements

Journey into the realm of deep learning and embrace the challenges, opportunities, and transformation of stock market analysis. Deep learning helps foresee market trends with increased accuracy. With advancements in deep learning, new opportunities in styles, tools, and techniques evolve and embrace data-driven insights with theories and practical applications. Learn about designing, training, and applying predictive models with rigorous attention to detail. This book offers critical thinking skills and the cultivation of discerning approaches to market analysis. This Book Discusses - Delves into the development of an ensemble model for stock market prediction, combining Long Short-Term Memory and autoregressive Integrated Moving Average - Explains rapid expansion of quantum computing technologies which change software engineering and addresses the challenges of literate analysis using data from several libraries - Provides an overview of deep learning techniques for forecasting stock market trends and examines their effectiveness across different time frames and market conditions - Explores applications and implications of various models for causality, volatility, and co-integration in stock markets, offering insights to investors and policymakers

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  • Språk:
  • Engelska
  • ISBN:
  • 9781394214303
  • Format:
  • Inbunden
  • Sidor:
  • 496
  • Utgiven:
  • 19. april 2024
  • Vikt:
  • 989 g.
Leveranstid: 2-4 veckor
Förväntad leverans: 13. oktober 2025

Beskrivning av Deep Learning Tools for Predicting Stock Market Movements

Journey into the realm of deep learning and embrace the challenges, opportunities, and transformation of stock market analysis. Deep learning helps foresee market trends with increased accuracy. With advancements in deep learning, new opportunities in styles, tools, and techniques evolve and embrace data-driven insights with theories and practical applications. Learn about designing, training, and applying predictive models with rigorous attention to detail. This book offers critical thinking skills and the cultivation of discerning approaches to market analysis. This Book Discusses - Delves into the development of an ensemble model for stock market prediction, combining Long Short-Term Memory and autoregressive Integrated Moving Average - Explains rapid expansion of quantum computing technologies which change software engineering and addresses the challenges of literate analysis using data from several libraries - Provides an overview of deep learning techniques for forecasting stock market trends and examines their effectiveness across different time frames and market conditions - Explores applications and implications of various models for causality, volatility, and co-integration in stock markets, offering insights to investors and policymakers

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