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Statistical Tools for Finance and Insurance (Paperback)
  • Statistical Tools for Finance and Insurance (Paperback)
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Statistical Tools for Finance and Insurance (Paperback)

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£119.99
Paperback 420 Pages / Published: 23/03/2011
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Statistical Tools for Finance and Insurance presents ready-to-use solutions, theoretical developments and method construction for many practical problems in quantitative finance and insurance. Written by practitioners and leading academics in the field, this book offers a unique combination of topics from which every market analyst and risk manager will benefit.

Features of the significantly enlarged and revised second edition:

Offers insight into new methods and the applicability of the stochastic technologyProvides the tools, instruments and (online) algorithms for recent techniques in quantitative finance and modern treatments in insurance calculationsCovers topics such as
- expected shortfall for heavy tailed and mixture distributions*
- pricing of variance swaps*
- volatility smile calibration in FX markets
- pricing of catastrophe bonds and temperature derivatives*
- building loss models and ruin probability approximation
- insurance pricing with GLM*
- equity linked retirement plans*(new topics in the second edition marked with*)Presents extensive examples

Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
ISBN: 9783642180613
Number of pages: 420
Weight: 646 g
Dimensions: 235 x 155 x 25 mm
Edition: 2nd ed. 2011


MEDIA REVIEWS

From the reviews of the second edition:

"Individual papers in this book could easily be considered for publication in many fine journals of finance ... . In all the papers, the documentation is well done, with a good deal of simulation studies to exemplify the processes under consideration. I would recommend this book for the library of serious researchers in field of the economic analysis of financial markets as well as those in statistical research in applied fields. Mathematical economists as well as statistical researchers will find the volume useful ... ." (Jeffrey E. Jarrett, Technometrics, Vol. 54 (1), February, 2012)

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