Abstract:Stochastic volatility models of the Ornstein-Uhlenbeck type possess authentic capability of capturing some stylized features of financial time series. In this work we investigate this class of models from the viewpoint of derivative asset analysis. We discuss topics related to the incompleteness of this type of markets. In particular, for structure preserving martingale measures, we derive the price of simple European-style contracts in closed form. Furthermore, the range of viable prices is determined and an … Show more
“…In particular, note that the reasoning for the Brownian motions W and W V goes along the lines of the proof of Proposition 1 and the reasoning for the jump part follows from Nicolato and Venardos (2003). Additionally, we deduce the independence of L and W V * under P * from Sato (1999, Theorem 19.3).…”
This paper proposes the new concept of stochastic leverage in stochastic volatility models. Stochastic leverage refers to a stochastic process which replaces the classical constant correlation parameter between the asset return and the stochastic volatility process. We provide a systematic treatment of stochastic leverage and propose to model the stochastic leverage effect explicitly, e.g. by means of a linear transformation of a Jacobi process. Such models are both analytically tractable and allow for a direct economic interpretation. In particular, we propose two new stochastic volatility models which allow for a stochastic leverage effect: the generalised Heston model and the generalised Barndorff-Nielsen & Shephard model. We investigate the impact of a stochastic leverage effect in the risk neutral world by focusing on implied volatilities generated by option prices derived from our new models. Furthermore, we give a detailed account on statistical properties of the new models.
“…In particular, note that the reasoning for the Brownian motions W and W V goes along the lines of the proof of Proposition 1 and the reasoning for the jump part follows from Nicolato and Venardos (2003). Additionally, we deduce the independence of L and W V * under P * from Sato (1999, Theorem 19.3).…”
This paper proposes the new concept of stochastic leverage in stochastic volatility models. Stochastic leverage refers to a stochastic process which replaces the classical constant correlation parameter between the asset return and the stochastic volatility process. We provide a systematic treatment of stochastic leverage and propose to model the stochastic leverage effect explicitly, e.g. by means of a linear transformation of a Jacobi process. Such models are both analytically tractable and allow for a direct economic interpretation. In particular, we propose two new stochastic volatility models which allow for a stochastic leverage effect: the generalised Heston model and the generalised Barndorff-Nielsen & Shephard model. We investigate the impact of a stochastic leverage effect in the risk neutral world by focusing on implied volatilities generated by option prices derived from our new models. Furthermore, we give a detailed account on statistical properties of the new models.
“…For a discussion about the existence of the risk-neutral measures in BNS model, see Nicolato and Vernardos (2003) and Hubalek and Sgarra (2009).…”
Section: Ou-sv and Bns Modelsmentioning
confidence: 99%
“…Some applications, have been obtained since then. Nicolato and Vernardos (2003) studied the option pricing problem in that setting for particular cases of the nonGaussian OU-SV models. More recently, Kallsen and Pauwels (2010) obtained the variance optimal hedging, and Benth (2011) used the BNS model to study commodity spot prices.…”
We find necessary and sufficient conditions for the market symmetry property, introduced by Fajardo and Mordecki (Quant Finance 6(3): [219][220][221][222][223][224][225][226][227] 2006), to hold in the Ornstein-Uhlenbeck stochastic volatility model, henceforth OU-SV. In particular, we address the non-Gaussian OU-SV model proposed by Barndorff-Nielsen and Shephard (J R Stat Soc B 63(Part 2): 2001). Also, we prove the Bates' rule for these models.
“…From the perspective of implied volatilities on options we see that volatilities on the S&P 500 index went above 34% in October of 2002 and were down to below 17% by January of 2004. This recognition has spurred the development of stochastic volatility models for pricing derivative contracts, beginning with the Heston (1993) (Carr et al 2003;Niccolato and Venardos 2003) or driving the volatility ( BarndorffNielsen and Shephard 2001;Duffie et al 2000).…”
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