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

Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, and risk analysts will explore Python-based machine learning and deep learning models for assessing financial risk. You'll learn how to compare results from ML models with results obtained by traditional financial risk models. Author Abdullah Karasan helps you explore the theory behind financial risk assessment before diving into the differences between traditional and ML models. 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 Revisit and improve market risk models (VaR and expected shortfall) using machine learning techniques Develop a credit risk based on a clustering technique for risk bucketing, then apply Bayesian estimation, Markov chain, and other ML models Capture different aspects of liquidity with a Gaussian mixture model Use machine learning models for fraud detection Identify corporate risk using the stock price crash metric Explore a synthetic data generation process to employ in financial risk

General

Imprint:	O'Reilly Media
Country of origin:	United States
Release date:	December 2021
Authors:	Abdullah Karasan
Dimensions:	232 x 178 x 20mm (L x W x T)
Format:	Paperback
Pages:	350
ISBN-13:	978-1-4920-8525-6
Categories:	Books Promotions
LSN:	1-4920-8525-1
Barcode:	9781492085256

Is the information for this product incomplete, wrong or inappropriate? Let us know about it.

Does this product have an incorrect or missing image? Send us a new image.

Is this product missing categories? Add more categories.

Review This Product

No reviews yet - be the first to create one!