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Machine Learning for Financial Risk Management with Python - by Abdullah Karasan (Paperback)

Machine Learning for Financial Risk Management with Python - by  Abdullah Karasan (Paperback) - 1 of 1
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About this item

Highlights

  • Financial risk management is quickly evolving with the help of artificial intelligence.
  • About the Author: Abdullah Karasan was born in Berlin, Germany.
  • 331 Pages
  • Computers + Internet,

Description



About the Book



"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"--



Book Synopsis



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



About the Author



Abdullah Karasan was born in Berlin, Germany. After studying economics and business administration, he obtained his master's degree in applied economics from the University of Michigan, Ann Arbor, and his PhD in financial mathematics from the Middle East Technical University, Ankara. He is a former Treasury employee of Turkey and currently works as a principal data scientist at Magnimind and as a lecturer at the University of Maryland, Baltimore. He has also published several papers in the field of financial data science.

Dimensions (Overall): 9.19 Inches (H) x 7.0 Inches (W) x .7 Inches (D)
Weight: 1.17 Pounds
Suggested Age: 22 Years and Up
Number of Pages: 331
Genre: Computers + Internet
Publisher: O'Reilly Media
Format: Paperback
Author: Abdullah Karasan
Language: English
Street Date: January 11, 2022
TCIN: 84899387
UPC: 9781492085256
Item Number (DPCI): 247-31-8613
Origin: Made in the USA or Imported
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Shipping details

Estimated ship dimensions: 0.7 inches length x 7 inches width x 9.19 inches height
Estimated ship weight: 1.17 pounds
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