Stochastic Volatility Modeling

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A01=Lorenzo Bergomi
advanced volatility modelling applications
Atm Volatility
Author_Lorenzo Bergomi
Category=KCH
Category=KFFM
Category=PBW
eq_bestseller
eq_business-finance-law
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
equity derivatives
financial mathematics
Forward Variances
Forward Volatilities
Forward-start options
Heston Model
Implied Volatilities
Instantaneous Volatility
L? Models
Levy models
Local volatility
Local Volatility Function
Local Volatility Model
local-stochastic volatility models
Log Contract
Market Smile
Maturity T2
Maturity Ti
model calibration techniques
modeling of derivatives
Multi-asset stochastic volatility
option pricing theory
Quadratic Variation
quantitative finance
risk management
Set Iii
Stochastic Volatility
Stochastic Volatility Models
Vanilla Option
Vanilla Option Prices
variance swaps
Versus
VIX Futures
Volatility Correlation
Volatility Model
Volatility surface

Product details

  • ISBN 9781482244069
  • Weight: 940g
  • Dimensions: 156 x 234mm
  • Publication Date: 05 Jan 2016
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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Packed with insights, Lorenzo Bergomi’s Stochastic Volatility Modeling explains how stochastic volatility is used to address issues arising in the modeling of derivatives, including:

  • Which trading issues do we tackle with stochastic volatility?
  • How do we design models and assess their relevance?
  • How do we tell which models are usable and when does calibration make sense?

This manual covers the practicalities of modeling local volatility, stochastic volatility, local-stochastic volatility, and multi-asset stochastic volatility. In the course of this exploration, the author, Risk’s 2009 Quant of the Year and a leading contributor to volatility modeling, draws on his experience as head quant in Société Générale’s equity derivatives division. Clear and straightforward, the book takes readers through various modeling challenges, all originating in actual trading/hedging issues, with a focus on the practical consequences of modeling choices.

Lorenzo Bergomi heads the quantitative research group at Société Générale, covering all asset classes. A quant for over 15 years, he is well known for his pioneering work on stochastic volatility modeling, some of which has appeared in the Smile Dynamics series of articles in Risk magazine. He was also the magazine’s 2009 Quant of the Year. Originally trained as an electrical engineer and with a PhD in theoretical physics, he was active as a physicist in the condensed matter theory group at IphT, CEA, before moving to finance.

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