Quantitative Risk Management Using Python (Paperback)
Language: English
Published by APress, Berkley, 2025
- Softcover
- New
Seller: CitiRetail, Stevenage, United KingdomCitiRetail
AbeBooks seller since June 29, 2022
Condition: New
£ 60.99
Quantity: 1 available
Add to basketItem description from seller
Paperback. 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, youll examine common hedging strategies used to manage investment positions, along with practical implementations on evaluating risk-adjusted, as well as downside risk measures. Finally, youll 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.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 ForFinance 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. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…
Seller Inventory # 9798868815294
- Title
- Quantitative Risk Management Using Python (Paperback)
- Author
- Peng Liu
- Publisher
- APress, Berkley
- Publication year
- 2025
- Condition
- new
- Binding
- Paperback
- Language
- English
- ISBN 13
- 9798868815294
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.
CitiRetail
Stevenage, United Kingdom
AbeBooks seller since June 29, 2022
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