The Concepts and Practice of Mathematical Finance

The Concepts and Practice of Mathematical Finance
Author: Mark Suresh Joshi
Publisher: Cambridge University Press
Total Pages: 496
Release: 2003-12-24
Genre: Business & Economics
ISBN: 9780521823555

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
Total Pages:
Release: 2020-01-01
Genre: Business & Economics
ISBN: 9866286754

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
Total Pages: 698
Release: 2022-05-19
Genre: Business & Economics
ISBN: 1000582302

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
Total Pages: 451
Release: 2015-05-06
Genre: Business & Economics
ISBN: 1118738403

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
Total Pages: 314
Release: 2006-08-07
Genre: Mathematics
ISBN: 3540279261

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
Total Pages: 1008
Release: 2016-05-10
Genre: Business & Economics
ISBN: 9814571253

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
Total Pages:
Release: 2018-01-01
Genre: Business & Economics
ISBN: 9866286738

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
Total Pages: 270
Release: 2004
Genre: Business & Economics
ISBN: 9783540406044

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:
Total Pages: 766
Release: 2018-05-28
Genre:
ISBN: 9781732235601

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.