Implementing Machine Learning for Finance

Idioma: inglés

Editorial: APress, US, 2021

1484271092 / 9781484271094

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Librería: Rarewaves USA United, HEBRON, KY, Estados Unidos de AmericaRarewaves USA United

Vendedor de 5 estrellas

Vendedor de IberLibro desde 20 de junio de 2025

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Condición: Nuevo

EUR 47,80

Envío por EUR 44,58 
Se envía dentro de Estados Unidos de America

Cantidad disponible: 8 disponibles

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Descripción del artículo del vendedor

Bring together machine learning (ML) and deep learning (DL) in financial trading, with an emphasis on investment management. This book explains systematic approaches to investment portfolio management, risk analysis, and performance analysis, including predictive analytics using data science procedures.The book introduces pattern recognition and future price forecasting that exerts effects on time series analysis models, such as the Autoregressive Integrated Moving Average (ARIMA) model, Seasonal ARIMA (SARIMA) model, and Additive model, and it covers the Least Squares model and the Long Short-Term Memory (LSTM) model. It presents hidden pattern recognition and market regime prediction applying the Gaussian Hidden Markov Model. The book covers the practical application of the K-Means model in stock clustering. It establishes the practical application of the Variance-Covariance method and Simulation method (using Monte Carlo Simulation) for value at risk estimation. It also includes market direction classification using both the Logistic classifier and the Multilayer Perceptron classifier. Finally, the book presents performance and risk analysis for investment portfolios.By the end of this book, you should be able to explain how algorithmic trading works and its practical application in the real world, and know how to apply supervised and unsupervised ML and DL models to bolster investment decision making and implement and optimize investment strategies and systems.What You Will LearnUnderstand the fundamentals of the financial market and algorithmic trading, as well as supervised and unsupervised learning models that are appropriate for systematic investment portfolio managementKnow the concepts of feature engineering, data visualization, and hyperparameter optimizationDesign, build, and test supervised and unsupervised ML and DL modelsDiscover seasonality, trends, and market regimes, simulating a change in the market and investment strategy problems and predicting market direction and pricesStructure and optimize an investment portfolio with preeminent asset classes and measure the underlying riskWho This Book Is ForBeginning and intermediate data scientists, machine learning engineers, business executives, and finance professionals (such as investment analysts and traders).…

N° de ref. del artículo LU-9781484271094

Título
Implementing Machine Learning for Finance
Autor
Tshepo Chris Nokeri
Editorial
APress, US
Año de publicación
2021
Estado
New
Encuadernación
Paperback
Idioma
inglés
ISBN 10
1484271092
ISBN 13
9781484271094

Rarewaves USA United

HEBRON, KY, Estados Unidos de America

Vendedor de 5 estrellas

Vendedor de IberLibro desde 20 de junio de 2025

Tarifas de envío en Estados Unidos de America

ArtículoDe 30 a 30 días hábilesDe 14 a 14 días hábiles
Primer artículoEUR 44,58EUR 59,73
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Información empresarial del vendedor

Rarewaves USA

10100 West Sample Road, Ste 101
Coral Springs, FL Estados Unidos de America 33065