Machine Learning for Financial Risk Management with Python: Algorithms for Modeling Risk (Paperback)

Abdullah Karasan

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商品描述

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

商品描述(中文翻譯)

金融風險管理正快速發展,人工智慧的幫助下更加迅猛。這本實用書籍專為開發人員、程式設計師、工程師、金融分析師、風險分析師以及量化和演算法分析師而寫,介紹了基於Python的機器學習和深度學習模型,用於評估金融風險。通過建立實踐中的基於人工智慧的金融建模技能,您將學習如何用機器學習模型取代傳統的金融風險模型。

作者Abdullah Karasan在深入介紹金融風險建模理論之前,幫助您探索了在Python中應用機器學習模型進行金融風險建模的實際方法。這本書將幫助您:

- 檢視傳統時間序列應用並將其與深度學習模型進行比較
- 探索使用支持向量回歸、神經網絡和深度學習來測量風險程度的波動性建模
- 使用機器學習技術改進市場風險模型(VaR和ES),並包括流動性維度
- 使用聚類和貝葉斯方法進行信用風險分析
- 使用高斯混合模型和Copula模型捕捉流動性風險的不同方面
- 使用機器學習模型進行欺詐檢測
- 預測股價崩盤並使用機器學習模型識別其決定因素

作者簡介

Abdullah Karasan was born in Berlin, Germany. After he studied Economics and Business Administration at Gazi University-Ankara, he obtained his master's degree from the University of Michigan-Ann Arbor and his PhD in Financial Mathematics from Middle East Technical University (METU)-Ankara. He worked as a Treasury Controller at the Undersecretariat of Treasury of Turkey. More recently, he has started to work as a Senior Data Science consultant and instructor for companies in Turkey and the USA. Currently, he is a Data Science consultant at Datajarlabs and Data Science mentor at Thinkful.

作者簡介(中文翻譯)

Abdullah Karasan在德國柏林出生。在他在安卡拉加齊大學學習經濟學和工商管理之後,他在密歇根大學安娜堡分校獲得碩士學位,並在中東技術大學(METU)安卡拉獲得金融數學博士學位。他曾在土耳其財政部擔任財務控制員。最近,他開始在土耳其和美國的公司擔任高級數據科學顧問和講師。目前,他是Datajarlabs的數據科學顧問和Thinkful的數據科學導師。