Quantitative Risk Management Using Python
Language: English
Published by Apress, Apress Sep 2025, 2025
- Softcover
- New
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
AbeBooks seller since January 11, 2012
Condition: New
£ 52.00
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Add to basketItem description from seller
This item is printed on demand - it takes 3-4 days longer - Neuware -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.What You Will LearnExplore 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. 260 pp. Englisch.…
Seller Inventory # 9798868815294
- Title
- Quantitative Risk Management Using Python
- Author
- Peng Liu
- Publisher
- Apress, Apress Sep 2025
- Publication year
- 2025
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 13
- 9798868815294
- Item weight
- 400 grams
- Dimensions
- 235x155x15 mm
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.
What You Will Learn
- 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.
Who This Book Is For
Finance professionals, academics, and students seeking to deepen their understanding of Quantitative Risk Management using Python, especially those interested in navigating the intricate domains of credit, market and model risk within the financial sector and beyond.
"Synopsis" may belong to another edition of this title.
About the Author
Peng Liu is an Assistant Professor of Quantitative Finance (Practice) at Singapore Management University and an adjunct researcher at the National University of Singapore. He holds a Ph.D. in statistics from the National University of Singapore and has over 10 years of working experience across the banking, technology, and hospitality industries. Peng is the author of Bayesian Optimization (Apress, 2023) and Quantitative Trading Strategies Using Python (Apress, 2023)
"About the title" may belong to another edition of this title.
BuchWeltWeit Ludwig Meier e.K.
Bergisch Gladbach, Germany
AbeBooks seller since January 11, 2012
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