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Stochastic Volatility of Volatility and Variance Risk Premia
SSRN Electronic Journal, 2011This article introduces a new class of stochastic volatility models which allows for stochastic volatility of volatility (SVV): Volatility modulated non-Gaussian Ornstein--Uhlenbeck (VMOU) processes. Various probabilistic properties of (integrated) VMOU processes are presented.
Barndorff-nielsen, O.E., Veraart, A.E.D.
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Structural Stochastic Volatility
SSRN Electronic Journal, 2020We use a local (in time) expansion of the characteristic function of the equity process in continuous time to derive short-maturity option prices. The prices, along with data on short-maturity options, are employed to jointly identify equity characteristics (spot volatility, spot leverage and spot volatility of volatility) which have been the focus of ...
Nicola Fusari +2 more
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2008
Stochastic volatility (SV) is the main concept used in the fields of financial economics and mathematical finance to deal with the endemic time-varying volatility and codependence found in financial markets. Such dependence has been known for a long time; early commentators include Mandelbrot (1963) and Officer (1973). It was also clear to the founding
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Stochastic volatility (SV) is the main concept used in the fields of financial economics and mathematical finance to deal with the endemic time-varying volatility and codependence found in financial markets. Such dependence has been known for a long time; early commentators include Mandelbrot (1963) and Officer (1973). It was also clear to the founding
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Estimation of stochastic volatility with LRD
Mathematics and Computers in Simulation, 2008Understanding the behaviour of market prices is not simple. Stock market prices tend to have complicated distributions with strong skewness and fat tails. One important step in forecasting tomorrow's price is to estimate the volatility, i.e. how much tomorrow's price is expected to differ from today's price.
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Computing the implied volatility in stochastic volatility models
Communications on Pure and Applied Mathematics, 2004zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Igor Florent +2 more
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Estimation of Stochastic Volatility Models
2002The stochastic volatility model and the problems related to their estimation are considered. After reviewing the most popular estimation procedures, it is illustrated how to overcome the difficulty of evaluating and maximizing the likelihood, a high-dimensional integral, using a quadrature method.
BARTOLUCCI, Francesco, De Luca G.
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2016
Stochastic volatility models are used when the option price is very sensitive to volatility (smile) moves, and when they cannot be explained by the evolution of the underlying asset itself, see e.g. [34]. This is typically the case for exotic options.
Jean-François Chassagneux +1 more
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Stochastic volatility models are used when the option price is very sensitive to volatility (smile) moves, and when they cannot be explained by the evolution of the underlying asset itself, see e.g. [34]. This is typically the case for exotic options.
Jean-François Chassagneux +1 more
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1996
Publisher Summary The class of stochastic volatility (SV) models has its roots in both, mathematical finance and financial econometrics. In fact, several variations of SV models originated from research looking at very different issues. Volatility plays a central role in the pricing of derivative securities. The Black-Scholes model for the pricing of
Eric Renault +2 more
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Publisher Summary The class of stochastic volatility (SV) models has its roots in both, mathematical finance and financial econometrics. In fact, several variations of SV models originated from research looking at very different issues. Volatility plays a central role in the pricing of derivative securities. The Black-Scholes model for the pricing of
Eric Renault +2 more
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Stochastic Volatility Processes [PDF]
, 2013 In a stochastic volatility process, the positivity and mean reversion of the volatility should be enforced. The mean reversion can be achieved by the drift, equivalent to an Ornstein–Uhlenbeck process. The positivity can be enforced either by an exponential or by taming down the stochastic term by the volatility as done in the Heston process.
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Stochastic Volatility for Real
SSRN Electronic Journal, 2006We combine classical ideas of separable volatility structures in the HJM framework with the latest techniques for calibration of stochastic volatility models and create a new class of efficient multi-factor term structure models with stochastic volatility.
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