Stochastic volatility is the main concept used in the fields of financial economics and mathematical finance to deal with time-varying volatility in financial markets. This book brings together some of the main papers that have influenced the field of the econometrics of stochastic volatility, and shows that the development of this subject has been highly multidisciplinary, with results drawn from financial economics, probability theory, and econometrics, blending to produce methods and models that have aided our understanding of the realistic pricing of options, efficient asset allocation, and accurate risk assessment. A lengthy introduction by the editor connects the papers with the literature. Contributors to this volume - Contributors: Torben Andersen, Northwestern University; Ole E. Barndorff-Nielsen, University of Aarhus; Tim Bollerslev, Duke University; Mikhail Chernov; Siddhartha Chib, Washington University in St. Louis; Peter Clark, University of California, Davis; Fabienne Comte, Universite Rene Descartes- Paris 5; Frank Diebold, University of Pennsylvania; Dean Foster, University of Pennsylvania; A Ronald Gallant, Duke University; Eric Ghysels, University of North Carolina - Chapel Hill; Andrew Harvey, University of Cambridge; Steven Heston, University of Maryland; David Hsieh, Duke University; John Hull, University of Toronto; Eric Jacquier, H.E.C. MONTREAL; Sangjoon Kim, RBS Securities Japan Limited; Paul Labys, Charles River Associates; Angelo Melino, University of Toronto; Daniel Nelson; Marc Nerlove, University of Maryland; Nicholas Polson, University of Chicago; Eric Renault, University of Montreal; Peter Rossi, University of Chicago; Esther Ruiz, Universidad Carlos III de Madrid; Barr Rosenberg, AXA Rosenberg Investment Management; Neil Shephard, Nuffield College, University of Oxford; Stephen Taylor, Lancaster University; George Tauchen, Duke University; Stuart Turnbull, University of Houston; Alan White, University of Toronto.
Shephard, Neil (ed.), 2005.
"Stochastic Volatility: Selected Readings,"
Oxford University Press, number 9780199257201.
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