Custom cover image
Custom cover image

Quantitative risk management using Python : an essential guide for managing market, credit, and model risk / Peng Liu

By: Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Publisher: [Berkeley, CA] ; New York, NY : Apress, [2025]Copyright date: © 2025Description: 1 Online-Ressource (xx, 238 Seiten) : IllustrationenISBN:
  • 9798868815300
Subject(s): Additional physical formats: 9798868815294 | 9798868815317 | Erscheint auch als: 9798868815294 Druck-Ausgabe | Erscheint auch als: 9798868815317 Druck-AusgabeDDC classification:
  • 005.133 23
DOI: DOI: 10.1007/979-8-8688-1530-0Online resources: Summary: Chapter 1: Introduction to Quantitative Risk Management -- Chapter 2: Fundamentals of Risk and Return in Finance -- Chapter 3: Managing Credit Risk -- Chapter 4: Managing Market Risk -- Chapter 5: Risk Management Using Financial Derivatives -- Chapter6: Static and Dynamic Hedging -- Chapter 7: Managing Model Risk in Finance.Summary: Gain an understanding of various financial risks, the benefits of portfolio diversification, and the fundamental trade-off between risk and return. This book takes an in-depth journey into the world of quantitative risk management using Python, focusing on credit and market risk, with an extension to model risk. You'll start by reviewing the different types of financial risk, the benefit of diversification in a portfolio, and the fundamental trade-off between risk and return. The book then offers an in-depth look at managing credit and market risk in today's dynamic markets, all with practical Python implementations. Moving on, you’ll examine common hedging strategies used to manage investment positions, along with practical implementations on evaluating risk-adjusted, as well as downside risk measures. Finally, you’ll be introduced to common risks related to the development and use of machine learning models in finance. Whether you're a finance professional, academic, or student, Quantitative Risk Management Using Python will empower you to make informed decisions in today's complex financial landscape. You will: Explore techniques to assess and manage the risk of default by borrowers or counterparties. Identify, measure, and mitigate risks arising from fluctuations in market prices. Understand how derivatives can be employed for risk management purposes. Delve into both static and dynamic hedging techniques to protect investment positions, including practical applications for evaluating risk-adjusted and downside risk measures. Identify and address risks associated with the development and deployment of machine learning models in financial contexts. .PPN: PPN: 1935480073Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-CWD | ZDB-2-SXPC
No physical items for this record

Barrierefreier Inhalt: PDF/UA-1. Table of contents navigation. Single logical reading order. Short alternative textual descriptions. Use of color is not sole means of conveying information. Use of high contrast between text and background color. Next / Previous structural navigation. All non-decorative content supports reading without sight

Anmerkungen zur Barrierefreiheit: This PDF has been created in accordance with the PDF/UA-1 standard to enhance accessibility, including screen reader support, described non-text content (images, graphs), bookmarks for easy navigation, keyboard-friendly links and forms and searchable, selectable text. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. Please note that a more accessible version of this eBook is available as ePub.. No reading system accessibility options actively disabled. Publisher contact for further accessibility information: accessibilitysupport@springernature.com