The Concepts and Practice of Mathematical Finance
The Concepts and Practice of Mathematical Finance

Author: Mark Suresh Joshi

Publisher: Cambridge University Press

Published: 2003-12-24

Total Pages: 496

ISBN-13: 9780521823555

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For those starting out as practitioners of mathematical finance, this is an ideal introduction. It provides the reader with a clear understanding of the intuition behind derivatives pricing, how models are implemented, and how they are used and adapted in practice. Strengths and weaknesses of different models, e.g. Black-Scholes, stochastic volatility, jump-diffusion and variance gamma, are examined. Both the theory and the implementation of the industry-standard LIBOR market model are considered in detail. Uniquely, the book includes extensive discussion of the ideas behind the models, and is even-handed in examining various approaches to the subject. Thus each pricing problem is solved using several methods. Worked examples and exercises, with answers, are provided in plenty, and computer projects are given for many problems. The author brings to this book a blend of practical experience and rigorous mathematical background, and supplies here the working knowledge needed to become a good quantitative analyst.

Advances in Quantitative Analysis of Finance and Accounting (New Series) Vol. 17
Advances in Quantitative Analysis of Finance and Accounting (New Series) Vol. 17

Author: Cheng F.Lee

Publisher: Center for PBBEFR & Ainosco Press

Published: 2020-01-01

Total Pages:

ISBN-13: 9866286754

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Advances in Quantitative Analysis of Finance and Accounting (New Series) is an annual publication designed to disseminate developments in the quantitative analysis of finance and accounting. The publication is a forum for statistical and quantitative analyses of issues in finance and accounting as well as applications of quantitative methods to problems in financial management, financial accounting, and business management. The objective is to promote interaction between academic research in finance and accounting and applied research in the financial community and the accounting profession.

Quantitative Finance with Python
Quantitative Finance with Python

Author: Chris Kelliher

Publisher: CRC Press

Published: 2022-05-19

Total Pages: 698

ISBN-13: 1000582302

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Quantitative Finance with Python: A Practical Guide to Investment Management, Trading and Financial Engineering bridges the gap between the theory of mathematical finance and the practical applications of these concepts for derivative pricing and portfolio management. The book provides students with a very hands-on, rigorous introduction to foundational topics in quant finance, such as options pricing, portfolio optimization and machine learning. Simultaneously, the reader benefits from a strong emphasis on the practical applications of these concepts for institutional investors. Features Useful as both a teaching resource and as a practical tool for professional investors. Ideal textbook for first year graduate students in quantitative finance programs, such as those in master’s programs in Mathematical Finance, Quant Finance or Financial Engineering. Includes a perspective on the future of quant finance techniques, and in particular covers some introductory concepts of Machine Learning. Free-to-access repository with Python codes available at www.routledge.com/ 9781032014432 and on https://github.com/lingyixu/Quant-Finance-With-Python-Code.

Quantitative Financial Risk Management
Quantitative Financial Risk Management

Author: Constantin Zopounidis

Publisher: John Wiley & Sons

Published: 2015-05-06

Total Pages: 451

ISBN-13: 1118738403

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A Comprehensive Guide to Quantitative Financial Risk Management Written by an international team of experts in the field, Quantitative Financial Risk Management: Theory and Practice provides an invaluable guide to the most recent and innovative research on the topics of financial risk management, portfolio management, credit risk modeling, and worldwide financial markets. This comprehensive text reviews the tools and concepts of financial management that draw on the practices of economics, accounting, statistics, econometrics, mathematics, stochastic processes, and computer science and technology. Using the information found in Quantitative Financial Risk Management can help professionals to better manage, monitor, and measure risk, especially in today's uncertain world of globalization, market volatility, and geo-political crisis. Quantitative Financial Risk Management delivers the information, tools, techniques, and most current research in the critical field of risk management. This text offers an essential guide for quantitative analysts, financial professionals, and academic scholars.

Tools for Computational Finance
Tools for Computational Finance

Author: Rüdiger U. Seydel

Publisher: Springer Science & Business Media

Published: 2006-08-07

Total Pages: 314

ISBN-13: 3540279261

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Tools for Computational Finance offers a clear explanation of computational issues arising in financial mathematics. The new third edition is thoroughly revised and significantly extended, including an extensive new section on analytic methods, focused mainly on interpolation approach and quadratic approximation. Other new material is devoted to risk-neutrality, early-exercise curves, multidimensional Black-Scholes models, the integral representation of options and the derivation of the Black-Scholes equation. New figures, more exercises, and expanded background material make this guide a real must-to-have for everyone working in the world of financial engineering.

Quantitative Finance And Risk Management: A Physicist's Approach (2nd Edition)
Quantitative Finance And Risk Management: A Physicist's Approach (2nd Edition)

Author: Jan W Dash

Publisher: World Scientific Publishing Company

Published: 2016-05-10

Total Pages: 1008

ISBN-13: 9814571253

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Written by a physicist with extensive experience as a risk/finance quant, this book treats a wide variety of topics. Presenting the theory and practice of quantitative finance and risk, it delves into the 'how to' and 'what it's like' aspects not covered in textbooks or papers. A 'Technical Index' indicates the mathematical level for each chapter.This second edition includes some new, expanded, and wide-ranging considerations for risk management: Climate Change and its long-term systemic risk; Markets in Crisis and the Reggeon Field Theory; 'Smart Monte Carlo' and American Monte Carlo; Trend Risk — time scales and risk, the Macro-Micro model, singular spectrum analysis; credit risk: counterparty risk and issuer risk; stressed correlations — new techniques; and Psychology and option models.Solid risk management topics from the first edition and valid today are included: standard/advanced theory and practice in fixed income, equities, and FX; quantitative finance and risk management — traditional/exotic derivatives, fat tails, advanced stressed VAR, model risk, numerical techniques, deals/portfolios, systems, data, economic capital, and a function toolkit; risk lab — the nuts and bolts of risk management from the desk to the enterprise; case studies of deals; Feynman path integrals, Green functions, and options; and 'Life as a Quant' — communication issues, sociology, stories, and advice.

Advances in Quantitative Analysis of Finance and Accounting (New Series) Vol．16
Advances in Quantitative Analysis of Finance and Accounting (New Series) Vol．16

Author: Cheng F. Lee

Publisher: Center for PBBEFR & Ainosco Press

Published: 2018-01-01

Total Pages:

ISBN-13: 9866286738

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Advances in Quantitative Analysis of Finance and Accounting (New Series) is an annual publication designed to disseminate developments in the quantitative analysis of finance and accounting. The publication is a forum for statistical and quantitative analyses of issues in finance and accounting as well as applications of quantitative methods to problems in financial management, financial accounting, and business management. The objective is to promote interaction between academic research in finance and accounting and applied research in the financial community and the accounting profession.

Tools for Computational Finance
Tools for Computational Finance

Author: Rüdiger Seydel

Publisher: Springer Science & Business Media

Published: 2004

Total Pages: 270

ISBN-13: 9783540406044

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This edition contains more material. The largest addition is a new section on jump processes (Section 1.9). The derivation of a related partial integro differential equation is included in Appendix A3. More material is devoted to Monte Carlo simulation. An algorithm for the standard workhorse of in verting the normal distribution is added to Appendix A7. New figures and more exercises are intended to improve the clarity at some places. Several further references give hints on more advanced material and on important developments. Many small changes are hoped to improve the readability of this book. Further I have made an effort to correct misprints and errors that I knew about. A new domain is being prepared to serve the needs of the computational finance community, and to provide complementary material to this book. The address of the domain is www.compfin.de The domain is under construction; it replaces the website address www . mi. uni koeln.de/numerik/compfin/. Suggestions and remarks both on this book and on the domain are most welcome.

A Quantitative Primer on Investments with R
A Quantitative Primer on Investments with R

Author: Dale W R Rosenthal

Publisher:

Published: 2018-05-28

Total Pages: 766

ISBN-13: 9781732235601

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A Quantitative Exploration of Investments -- So You Can Be a Better Analyst! Quantitative analysts and financial engineers often skip taking an investments course. Many would-be analysts take a less quantitative investments course. This omission robs them of the fundamental knowledge needed to create better, more profitable models. A Quantitative Primer on Investments with R fills that gap by taking a quantitative approach to investments and analyzing real data using R, the open source statistical computing language. This illuminates the commonalities among investment theories and builds intuition. This text collects the author's two decades of experience in finance -- from positions at Goldman Sachs, Morgan Stanley's Equity Trading Lab, and hedge fund Long-Term Capital Management to the quantitative background of a PhD in statistics, teaching at some of the world's top universities, and presenting research at central banks, regulatory agencies, and trading firms. The explanations, questions, and exercises have been tested over a decade and enabled many students to enter the world of quantitative finance and succeed.

Quantitative Risk Management
Quantitative Risk Management

Author: Alexander J. McNeil

Publisher: Princeton University Press

Published: 2015-05-26

Total Pages: 721

ISBN-13: 1400866286

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This book provides the most comprehensive treatment of the theoretical concepts and modelling techniques of quantitative risk management. Whether you are a financial risk analyst, actuary, regulator or student of quantitative finance, Quantitative Risk Management gives you the practical tools you need to solve real-world problems. Describing the latest advances in the field, Quantitative Risk Management covers the methods for market, credit and operational risk modelling. It places standard industry approaches on a more formal footing and explores key concepts such as loss distributions, risk measures and risk aggregation and allocation principles. The book's methodology draws on diverse quantitative disciplines, from mathematical finance and statistics to econometrics and actuarial mathematics. A primary theme throughout is the need to satisfactorily address extreme outcomes and the dependence of key risk drivers. Proven in the classroom, the book also covers advanced topics like credit derivatives. Fully revised and expanded to reflect developments in the field since the financial crisis Features shorter chapters to facilitate teaching and learning Provides enhanced coverage of Solvency II and insurance risk management and extended treatment of credit risk, including counterparty credit risk and CDO pricing Includes a new chapter on market risk and new material on risk measures and risk aggregation