Machine Learning for Financial Risk Management with Python

Machine Learning for Financial Risk Management with Python: Algorithms for Modeling Risk

eBook Details:

  • Paperback: 334 pages
  • Publisher: WOW! eBook (December 28, 2021)
  • Language: English
  • ISBN-10: 1492085251
  • ISBN-13: 978-1492085256

eBook Description:

Machine Learning for Financial Risk Management with Python: Algorithms for Modeling Risk

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.

With this Machine Learning for Financial Risk Management with Python 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

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.

Exclusive Offer! Order Profile Scribing Ruler Contour Gauge with Lock Adjustable Locking Precise Woodworking Measuring Gauge Measurement Tool, Precise Contour Gauge with Lock Now. Get Lowest Price & 60 Day Return Policy. Huge Discounts Available! Bravo Goods Special Offer Expires Soon.

DOWNLOAD

Leave a Reply

Your email address will not be published. Required fields are marked *