Search results for "stochastic volatility"

showing 6 items of 36 documents

European Option Pricing with Transaction Costs and Stochastic Volatility: an Asymptotic Analysis

2015

In this paper the valuation problem of a European call option in presence of both stochastic volatility and transaction costs is considered. In the limit of small transaction costs and fast mean reversion, an asymptotic expression for the option price is obtained. While the dominant term in the expansion it is shown to be the classical Black and Scholes solution, the correction terms appear at $O(\varepsilon^{1/2})$ and $O(\varepsilon)$. The optimal hedging strategy is then explicitly obtained for the Scott's model.

Transaction costAsymptotic analysisStochastic volatilityAsymptotic AnalysisApplied MathematicsStochastic VolatilityBlack–Scholes modelDynamical Systems (math.DS)Implied volatilityTransaction CostsFOS: Economics and businessOption Pricing; Stochastic Volatility; Transaction Costs; Asymptotic AnalysisValuation of optionstransaction costEconometricsMean reversionFOS: MathematicsCall optionPricing of Securities (q-fin.PR)Mathematics - Dynamical SystemsOption PricingSettore MAT/07 - Fisica MatematicaQuantitative Finance - Pricing of SecuritiesMathematics
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Empirical Study on the Relationship between the Cross-Correlation among Stocks and the Stocks' Volatility Clustering

2013

In this paper we discuss univariate and multivariate statistical properties of volatility with the aim of understanding how these two aspects are interrelated. Specifically, we focus on the relationship between the cross-correlation among stock's volatilities and the volatility clustering. Volatility clustering is related to the memory property of the volatility time-series and therefore to its predictability. Our results show that there exists a relationship between the level of predictability of any volatility time-series and the amount of its inter-dependence with other assets. In all considered cases, the more the asset is linked to other assets, the more its volatility keeps memory of …

financial instruments and regulation socio-economic networks stochastic processes clustering techniquesVolatility clusteringStochastic volatilityFinancial models with long-tailed distributions and volatility clusteringVolatility swapForward volatilityEconometricsVolatility smileEconomicsImplied volatilityVolatility risk premiumSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)SSRN Electronic Journal
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The Euro and Monetary Policy Transparency

2002

This paper focuses on a possible explanation for the weakness of the euro, namely the lack of transparency of the European Central Bank's (ECB) monetary policy. In order to obtain a time-varying measure of monetary policy uncertainty in both the U.S. and Euroland, we estimate a Stochastic Volatility model using policy-adjusted short-term interest rates. We also analyze directly the impact of higher uncertainty on the euro-dollar exchange rate. The empirical findings are in line with those of other studies, and show that the U.S. Fed is more transparent than the ECB. This results in higher volatility of European interest rates, capital outflows, and a weaker euro vis-a-vis the U.S. dollar.

monetary policy transparency; exchange ratesmonetary policy uncertainty stochastic volatilityExchange Rates; Interest Rates; Interest; Monetary Policy; Monetary; Policyjel:E52jel:E42monetary policy transparencyexchange ratesjel:F36jel:F33
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Reduced Order Models for Pricing European and American Options under Stochastic Volatility and Jump-Diffusion Models

2017

Abstract European options can be priced by solving parabolic partial(-integro) differential equations under stochastic volatility and jump-diffusion models like the Heston, Merton, and Bates models. American option prices can be obtained by solving linear complementary problems (LCPs) with the same operators. A finite difference discretization leads to a so-called full order model (FOM). Reduced order models (ROMs) are derived employing proper orthogonal decomposition (POD). The early exercise constraint of American options is enforced by a penalty on subset of grid points. The presented numerical experiments demonstrate that pricing with ROMs can be orders of magnitude faster within a give…

ta113Mathematical optimizationGeneral Computer ScienceStochastic volatilityDifferential equationEuropean optionMonte Carlo methods for option pricingJump diffusion010103 numerical & computational mathematics01 natural sciencesTheoretical Computer Science010101 applied mathematicsValuation of optionsModeling and Simulationlinear complementary problemRange (statistics)Asian optionreduced order modelFinite difference methods for option pricing0101 mathematicsAmerican optionoption pricingMathematicsJournal of Computational Science
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Reduced Order Models for Pricing American Options under Stochastic Volatility and Jump-diffusion Models

2016

American options can be priced by solving linear complementary problems (LCPs) with parabolic partial(-integro) differential operators under stochastic volatility and jump-diffusion models like Heston, Merton, and Bates models. These operators are discretized using finite difference methods leading to a so-called full order model (FOM). Here reduced order models (ROMs) are derived employing proper orthogonal decomposition (POD) and non negative matrix factorization (NNMF) in order to make pricing much faster within a given model parameter variation range. The numerical experiments demonstrate orders of magnitude faster pricing with ROMs. peerReviewed

ta113Mathematical optimizationStochastic volatilityDiscretizationComputer scienceJump diffusionFinite difference method010103 numerical & computational mathematics01 natural sciencesNon-negative matrix factorization010101 applied mathematicsValuation of optionslinear complementary problemRange (statistics)General Earth and Planetary SciencesApplied mathematicsreduced order modelFinite difference methods for option pricing0101 mathematicsAmerican optionoption pricingGeneral Environmental ScienceProcedia Computer Science
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Iterative Methods for Pricing American Options under the Bates Model

2013

We consider the numerical pricing of American options under the Bates model which adds log-normally distributed jumps for the asset value to the Heston stochastic volatility model. A linear complementarity problem (LCP) is formulated where partial derivatives are discretized using finite differences and the integral resulting from the jumps is evaluated using simple quadrature. A rapidly converging fixed point iteration is described for the LCP, where each iterate requires the solution of an LCP. These are easily solved using a projected algebraic multigrid (PAMG) method. The numerical experiments demonstrate the efficiency of the proposed approach. Furthermore, they show that the PAMG meth…

ta113Mathematical optimizationStochastic volatilityDiscretizationIterative methodComputer scienceFinite difference methodLinear complementarity problemIterative methodQuadrature (mathematics)Multigrid methodFixed-point iterationBates modelLinear complementarity problemGeneral Earth and Planetary SciencesPartial derivativeAmerican optionGeneral Environmental ScienceProcedia Computer Science
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