Volume I: Quantitative Methods in Finance Written by leading market risk academic, Professor Carol Alexander, Quantitative Methods in Finance forms part one of the Market Risk Analysis four volume set. Starting from the basics, this book helps readers to take the first step towards becoming a properly qualified financial risk manager and asset manager, roles that are currently in huge demand. Accessible to intelligent readers with a moderate understanding of mathematics at high school level or to anyone with a university degree in mathematics, physics or engineering, no prior knowledge of finance is necessary. Instead the emphasis is on understanding ideas rather than on mathematical rigour, meaning that this book offers a fast-track introduction to financial analysis for readers with some quantitative background, highlighting those areas of mathematics that are particularly relevant to solving problems in financial risk management and asset management. Unique to this book is a focus on both continuous and discrete time finance so that Quantitative Methods in Finance is not only about the application of mathematics to finance; it also explains, in very pedagogical terms, how the continuous time and discrete time finance disciplines meet, providing a comprehensive, highly accessible guide which will provide readers with the tools to start applying their knowledge immediately. All together, the Market Risk Analysis four volume set illustrates virtually every concept or formula with a practical, numerical example or a longer, empirical case study. Across all four volumes there are approximately 300 numerical and empirical examples, 400 graphs and figures and 30 case studies many of which are contained in interactive Excel spreadsheets available from the the accompanying CD-ROM . Empirical examples and case studies specific to this volume include: Principal component analysis of European equity indices; Calibration of Student t distribution by maximum likelihood; Orthogonal regression and estimation of equity factor models; Simulations of geometric Brownian motion, and of correlated Student t variables; Pricing European and American options with binomial trees, and European options with the Black-Scholes-Merton formula; Cubic spline fitting of yields curves and implied volatilities; Solution of Markowitz problem with no short sales and other constraints; Calculation of risk adjusted performance metrics including generalised Sharpe ratio, omega and kappa indices..
Book Details:
- Author: Carol Alexander
- ISBN: 9780470771020
- Year Published: 2008
- Pages: 318
- BISAC: BUS027000, BUSINESS & ECONOMICS/Finance
About the Book and Topic:
Volume I: Quantitative Methods in Finance Written by leading market risk academic, Professor Carol Alexander, Quantitative Methods in Finance forms part one of the Market Risk Analysis four volume set. Starting from the basics, this book helps readers to take the first step towards becoming a properly qualified financial risk manager and asset manager, roles that are currently in huge demand. Accessible to intelligent readers with a moderate understanding of mathematics at high school level or to anyone with a university degree in mathematics, physics or engineering, no prior knowledge of finance is necessary. Instead the emphasis is on understanding ideas rather than on mathematical rigour, meaning that this book offers a fast-track introduction to financial analysis for readers with some quantitative background, highlighting those areas of mathematics that are particularly relevant to solving problems in financial risk management and asset management. Unique to this book is a focus on both continuous and discrete time finance so that Quantitative Methods in Finance is not only about the application of mathematics to finance; it also explains, in very pedagogical terms, how the continuous time and discrete time finance disciplines meet, providing a comprehensive, highly accessible guide which will provide readers with the tools to start applying their knowledge immediately. All together, the Market Risk Analysis four volume set illustrates virtually every concept or formula with a practical, numerical example or a longer, empirical case study. Across all four volumes there are approximately 300 numerical and empirical examples, 400 graphs and figures and 30 case studies many of which are contained in interactive Excel spreadsheets available from the the accompanying CD-ROM . Empirical examples and case studies specific to this volume include: Principal component analysis of European equity indices; Calibration of Student t distribution by maximum likelihood; Orthogonal regression and estimation of equity factor models; Simulations of geometric Brownian motion, and of correlated Student t variables; Pricing European and American options with binomial trees, and European options with the Black-Scholes-Merton formula; Cubic spline fitting of yields curves and implied volatilities; Solution of Markowitz problem with no short sales and other constraints; Calculation of risk adjusted performance metrics including generalised Sharpe ratio, omega and kappa indices..
Mathematical finance is the branch of applied mathematics concerned with the financial markets. The subject has a close relationship with the discipline of financial economics, which is concerned with much of the underlying theory. Generally, mathematical finance will derive, and extend, the mathematical or numerical models suggested by financial economics. Thus, for example, while a financial economist might study the structural reasons why a company may have a certain share price, a financial mathematician may take the share price as a given, and attempt to use stochastic calculus to obtain the fair value of derivatives of the stock. In terms of practice, mathematical finance also overlaps heavily with the fields of financial engineering and computational finance. Arguably, all three are largely synonymous, although the latter two focus on application, while the former focuses on modelling and derivation; see Quantitative analyst.
AUTHOR TRACK RECORD: Authors previous work Market Models has sold 10,000 copies to date AUTHOR REPUTATION: Author is very well-respected and is recognized in both academic and practitioner communities PRACTICAL BOOK: Numerous real world applications throughout
About the Author
Carol Alexander, Reading UK is Professor of Risk Management and Director of Research at the ICMA Centre, Reading University, UK. Prior to this post, she held positions in both academia and financial institutions at: Gemente Universiteit in Amsterdam; UBS Phillips and Drew; The University of Sussex; Algorithmics Inc. and Nikko Global Holdings. Carol was a lecturer in Mathematics and Economics for 13 years at Sussex University. From 1996 to 1998 she also worked part-time in the industry, as Academic Director of Algorithmics, a large international enterprise-wide risk management software company. Following this, she worked briefly as full-time Director of Nikko Global Holdings, before returning to Academia. Carol has a PhD in Algebraic Number Theory and a first class BSc in Mathematics with Experimental Psychology from Sussex University and an MSc in Econometrics and Mathematical Economics from the London School of Economics. She holds an honorary professorship at the Academy of Economic Studies in Bucharest. She is Chair of the Academic Advisory Council of the Professional Risk Management InternationalAssociation (PRMIA) risk research advisor for the software company SAS, and director of 2021 solutions Carol has published numerous papers in international academic and professional journals. Her current research interests are in continuous and discrete time volatility and correlation analysis, hedge funds, multifactor pricing models and operational risk. She has edited several books, and is author of Market Models: A Guide to Financial Data Analysis (John Wiley 2001). Since 1990 the professional side of Carol’s career has focussed on developing mathematical models for risk management and investment analysis. Most of her consultancy work involves the design of software for risk management, portfolio optimization and trading.