Search results for "Monte Carlo methods for option pricing"

showing 3 items of 3 documents

European Option Pricing and Hedging with Both Fixed and Proportional Transaction Costs

2003

Abstract In this paper we provide a systematic treatment of the utility based option pricing and hedging approach in markets with both fixed and proportional transaction costs: we extend the framework developed by Davis et al. (SIAM J. Control Optim., 31 (1993) 470) and formulate the option pricing and hedging problem. We propose and implement a numerical procedure for computing option prices and corresponding optimal hedging strategies. We present a careful analysis of the optimal hedging strategy and elaborate on important differences between the exact hedging strategy and the asymptotic hedging strategy of Whalley and Wilmott (RISK 7 (1994) 82). We provide a simulation analysis in order …

Stochastic controlTransaction costEconomics and EconometricsMathematical optimizationControl and OptimizationApplied MathematicsMonte Carlo methods for option pricingjel:C61Implied volatilityjel:G13jel:G11option pricing transaction costs stochastic control Markov chain approximationMicroeconomicsVariable pricingOrder (business)Valuation of optionsEconomicsAsian optionFinite difference methods for option pricingSSRN Electronic Journal
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Model Based Monte Carlo Pricing of Energy and Temperature Quanto Options

2010

Weather derivatives have become very popular tools in weather risk management in recent years. One of the elements supporting their diffusion has been the increase in volatility observed on many energy markets. Among the several available contracts, Quanto options are now becoming very popular for a simple reason: they take into account the strong correlation between energy consumption and certain weather conditions, so enabling price and weather risk to be controlled at the same time. These products are more efficient and, in many cases, significantly cheaper than simpler plain vanilla options. Unfortunately, the specific features of energy and weather time series do not enable the use of …

Economics and EconometricsComputer scienceMonte Carlo methodTemperature levelBivariate analysisEnergy priceDynamic modelMicroeconomicsEconomicsEconometricsweather derivatives Quanto options pricing derivative pricing model simulation and forecast.Time seriesQuanto options; Temperature level; Energy price; Dynamic modelMonte Carlo methods for option pricingjel:C53Quanto optionsjel:C51Energy consumptionVariance (accounting)jel:C32Quantojel:G13weather derivatives; Quanto options pricing; derivative pricing; model simulation; forecastjel:L94jel:G17General Energyjel:Q54Binomial options pricing modelVolatility (finance)Futures contract
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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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