Machine learning for financial risk management with Python

Machine learning for financial risk management with Python: algorithms for modeling risk

by Karasan, Abdullah

Type Book
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Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, risk analysts, and quantitative and algorithmic analysts will examine Python-based machine learning and deep learning models for assessing financial risk. Building hands-on AI-based financial modeling skills, you'll learn how to replace traditional financial risk models with ML models. Author Abdullah Karasan helps you explore …

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Title Statements

  • Full title :Machine learning for financial risk management with Python : algorithms for modeling risk / Abdullah Karasan.

Summary

Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, risk analysts, and quantitative and algorithmic analysts will examine Python-based machine learning and deep learning models for assessing financial risk. Building hands-on AI-based financial modeling skills, you'll learn how to replace traditional financial risk models with ML models. Author Abdullah Karasan helps you explore the theory behind financial risk modeling before diving into practical ways of employing ML models in modeling financial risk using Python. With this book, you will: Review classical time series applications and compare them with deep learning models Explore volatility modeling to measure degrees of risk, using support vector regression, neural networks, and deep learning Improve market risk models (VaR and ES) using ML techniques and including liquidity dimension Develop a credit risk analysis using clustering and Bayesian approaches Capture different aspects of liquidity risk with a Gaussian mixture model and Copula model Use machine learning models for fraud detection Predict stock price crash and identify its determinants using machine learning models.

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Edition Statements

  • Publication Date:2022.

Publication Statements

  • Publisher(s):O'Reilly
  • Place of Publication:Cambridge
  • Language:eng
  • Publication Date:2022.

The Physical Object

  • Description:1 online resource (1 volume)

Edition Identifiers

  • ISBN:9781492085225, 1492085227, 9781492085201, 1492085200
  • oclc:on1289513846
  • LC Classification:HB615
  • Dewey Decimal:658.155

Subjects

Apprentissage automatique Finances -- Gestion du risque Financial risk management Machine learning Python (Computer program language) Python (Langage de programmation)

Writers

Karasan, Abdullah

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