Isbn: 9781492085256 - machine learning for financial risk management with python: algorithms for modeling risk (10 Ergebnisse)

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New. In English.

Zustand: New. 2021. Paperback. . . . . . Books ship from the US and Ireland.

Paperback. Zustand: Brand New. 350 pages. 9.19x7.00x0.70 inches. In Stock.

Zustand: New.

Zustand: NEW.

Zustand: New. 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 f.

Taschenbuch. Zustand: Neu. Machine Learning for Financial Risk Management with Python | Algorithms for Modeling Risk | Abdullah Karasan | Taschenbuch | Kartoniert / Broschiert | Englisch | 2021 | O'Reilly Media | EAN 9781492085256 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.…

Taschenbuch. Zustand: Neu. Neuware - 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.…