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Estimating and forecasting generalized fractional long memory stochastic volatility models
Peiris, Shelton; Asai, Manabu; McAleer, Michael - In: Journal of Risk and Financial Management 10 (2017) 4, pp. 1-16
corresponding statistical properties of this model, discuss the spectral likelihood estimation and investigate the finite sample …
Persistent link: https://www.econbiz.de/10012610989
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Estimating and Forecasting Generalized Fractional Long Memory Stochastic Volatility Models
Peiris, Shelton; Asai, Manabu; McAleer, Michael - 2016
. We examine the statistical properties of the new model, suggest using the spectral likelihood estimation for long memory …
Persistent link: https://www.econbiz.de/10011526121
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Estimating the Structural Credit Risk Model When Equity Prices Are Contaminated by Trading Noises
Duan, Jin-Chuan; Fulop, Andras - 2005
The transformed-data maximum likelihood estimation (MLE) method for struc- tural credit risk models developed by Duan … nonlinear filtering scheme. We devise a particle filtering algorithm that is practical for conducting the MLE estimation of the … simulation study is then conducted to ascertain the performance of the estimation method. …
Persistent link: https://www.econbiz.de/10010494319
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Pricing of options under different volatility models
Herzberg, Markus; Sibbertsen, Philipp - 2004
In this paper we compare the price of an option with one year maturity of the German stock index DAX for several volatility models including long memory and leverage effects. We compute the price by applying a present value scheme as well as the Black-Scholes and Hull-White formulas which...
Persistent link: https://www.econbiz.de/10010296646
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Why the Rotation Count Algorithm works
Lord, Roger; Kahl, Christian - 2006
The characteristic functions of many affine jump-diffusion models, such as Heston’s stochastic volatility model and all of its extensions, involve multivalued functions such as the complex logarithm. If we restrict the logarithm to its principal branch, as is done in most software packages,...
Persistent link: https://www.econbiz.de/10010325214
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Optimal Fourier Inversion in Semi-analytical Option Pricing
Lord, Roger; Kahl, Christian - 2006
At the time of writing this article, Fourier inversion is the computational method of choice for a fast and accurate calculation of plain vanilla option prices in models with an analytically available characteristic function. Shifting the contour of integration along the complex plane allows for...
Persistent link: https://www.econbiz.de/10010325539
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Asset pricing under information with stochastic volatility
Düring, Bertram - 2008
Based on a general specification of the asset speci?c pricing kernel, we develop a pricing model using an information process with stochastic volatility. We derive analytical asset and option pricing formulas. The asset prices in this rational expectations model exhibit crash-like, strong...
Persistent link: https://www.econbiz.de/10010266929
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The market price of risk for delivery periods: Pricing swaps and options in electricity markets
Kemper, Annika; Schmeck, Maren Diane; Balci, Anna KH. - 2020
In electricity markets, futures contracts typically function as a swap since they deliver the underlying over a period of time. In this paper, we introduce a market price for the delivery periods of electricity swaps, thereby opening an arbitrage-free pricing framework for derivatives based on...
Persistent link: https://www.econbiz.de/10012388852
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Pricing, risk and volatility in subordinated market models
Aguilar, Jean-Philippe; Kirkby, Justin Lars; Korbel, Jan - In: Risks 8 (2020) 4, pp. 1-27
We consider several market models, where time is subordinated to a stochastic process. These models are based on various time changes in the Lévy processes driving asset returns, or on fractional extensions of the diffusion equation; they were introduced to capture complex phenomena such as...
Persistent link: https://www.econbiz.de/10013200657
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Quantifying the model risk inherent in the calibration and recalibration of option pricing models
Feng, Yu; Rudd, Ralph; Baker, Christopher; Mashalaba, … - In: Risks 9 (2021) 1, pp. 1-20
We focus on two particular aspects of model risk: the inability of a chosen model to fit observed market prices at a given point in time (calibration error) and the model risk due to the recalibration of model parameters (in contradiction to the model assumptions). In this context, we use...
Persistent link: https://www.econbiz.de/10013200683