Présentation de l'éditeur
Quant of the Year 2000-2014 is a must-read for both aspiring quants and established practitioners. The new generation of quants will discover what the masters did in previous years and learn from their experience, while experienced quants will get a record of the key developments in the field more or less since the very beginning.
By their very nature the papers collected in Quant of the Year 2000-2014 cover the most important and relevant topics of financial engineering. Their chronological sequence gives a unique perspective on the development of the field, which cannot be obtained in any other way.
Quant of the Year 2000-2014 will empower readers to become familiar with the most important ideas regarding financial engineering presented since the year 2000, including the theoretical and practical answers to the problems posed by the financial crisis and its aftermath. Readers will learn how the best quants think and operate, what the most significant problems of the general field of financial engineering have been, and how to deal with the most important problems the quant community is now facing.
Each chapter represents a paper which is both a perennial classic and an industry standard which set the bar for all research in the quantitative finance field.
Smile Dynamics III: Lorenzo Bergomi (Société Générale)
Exposure Under Systemic Impact: Alexander Sokol (CompatibL) and Michael Pykhtin
Smoking Adjoints: Fast Monte Carlo Greeks: Paul Glasserman (Columbia Business School) and Michael Giles (University of Oxford)
Jumping Smiles: Leif Andersen (Bank of America Merrill Lynch) and Jesper Andreasen (Danske Bank)
Random Tranches: Michael Gordy and David Jones (Federal Reserve Board)
Quant of the Year 2000-2014 collates the biggest names in the financial modelling and quantitative finance field and their most significant research, with Alex’s analysis and unique perspective adding to their value. Readers will be able to implement the models described in the relevant chapters, and subsequently be better-equipped to deal with topics as diverse as the treatment of collateralized and uncollateralized derivatives, the calculation of the implied volatility surfaces, and the calibration of the local stochastic volatility models.