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Añadir al carritoTaschenbuch. Condición: Neu. Quantitative Risk Management Using Python | An Essential Guide for Managing Market, Credit, and Model Risk | Peng Liu | Taschenbuch | xx | Englisch | 2025 | Apress | EAN 9798868815294 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Añadir al carritoTaschenbuch. Condición: Neu. 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.
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. 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.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 260 pp. Englisch.
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.
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Añadir al carritoPaperback. Condición: new. 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.