This paper presents a lattice algorithm for pricing both European- and American-style moving average barrier options (MABOs). We develop a finite-dimensional partial differential equation (PDE) model for discretely mo...
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This paper presents a lattice algorithm for pricing both European- and American-style moving average barrier options (MABOs). We develop a finite-dimensional partial differential equation (PDE) model for discretely monitored MABOs and solve it numerically by using a forward shooting grid method. The modeling PDE for continuously monitored MABOs has infinite dimensions and cannot be solved directly by any existing numerical method. We find their approximate values indirectly by using an extrapolation technique with the prices of discretely monitored MABOs. Numerical experiments show that our algorithm is very efficient. (C) 2009 Elsevier B.V. All rights reserved.
An adaptive lattice algorithm based on third order cumulants is proposed. The computer simulation results are given to demonstrate the correctness and effectiveness of the proposed adaptive algorithm.
An adaptive lattice algorithm based on third order cumulants is proposed. The computer simulation results are given to demonstrate the correctness and effectiveness of the proposed adaptive algorithm.
We approximate d-variate functions from weighted Korobov spaces with the error of approximation defined in the L (a) sense. We study lattice algorithms and consider the worst-case setting in which the error is defined...
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We approximate d-variate functions from weighted Korobov spaces with the error of approximation defined in the L (a) sense. We study lattice algorithms and consider the worst-case setting in which the error is defined by its worst-case behavior over the unit ball of the space of functions. A lattice algorithm is specified by a generating (integer) vector. We propose three choices of such vectors, each corresponding to a different search criterion in the component-by-component construction. We present worst-case error bounds that go to zero polynomially with n (-1), where n is the number of function values used by the lattice algorithm. Under some assumptions on the weights of the function space, the worst-case error bounds are also polynomial in d, in which case we have (polynomial) tractability, or even independent of d, in which case we have strong (polynomial) tractability. We discuss the exponents of n (-1) and stress that we do not know if these exponents can be improved.
Geometrically speaking, ICA estimation can be completed through angle transformation. Hence, the paper presents a novel lattice ICA estimation algorithm based on schur-lattices. In contrast to other algorithms, a latt...
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ISBN:
(纸本)0780374908
Geometrically speaking, ICA estimation can be completed through angle transformation. Hence, the paper presents a novel lattice ICA estimation algorithm based on schur-lattices. In contrast to other algorithms, a lattice algorithm is more stable and convenient to be extended and implemented. Simulation results show satisfactory performance.
Geometrically speaking, ICA estimation can becompleted through angle transformation. Hence, the paperpresents a novel lattice ICA estimation algorithm based onschur-lattices. In contrast to other algorithms, a lattice...
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Geometrically speaking, ICA estimation can becompleted through angle transformation. Hence, the paperpresents a novel lattice ICA estimation algorithm based onschur-lattices. In contrast to other algorithms, a lattice algorithmis more stable and convenient to be extended and *** results show satisfactory performance.
Ritchken and Trevor (1999) proposed a lattice approach for pricing American options under discrete time-varying volatility GARCH frameworks. Even though the lattice approach worked well for the pricing of the GARCH op...
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Ritchken and Trevor (1999) proposed a lattice approach for pricing American options under discrete time-varying volatility GARCH frameworks. Even though the lattice approach worked well for the pricing of the GARCH options, it was inappropriate when the option price was computed on the lattice using standard backward recursive procedures, even if the concepts of Cakici and Topyan (2000) were incorporated. This paper shows how to correct the deficiency and that with our adjustment, the lattice method performs properly for option pricing under the GARCH process.
In this paper an efficient stochastic lattice approach is developed to price the American-style volatility options on the general stochastic volatility models. The stochastic volatility diffusion models are first disc...
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In this paper an efficient stochastic lattice approach is developed to price the American-style volatility options on the general stochastic volatility models. The stochastic volatility diffusion models are first discretized into forms that are amenable for designing the lattice approach, then the paths of the underlying volatility are generated by the lattice, and finally the valuation of the American volatility options is realized by the backward processes. One of the keys to the designing of the lattice approach is to derive the probability distributions of the underlying volatility on the lattice-nodes. Numerical analysis is given to confirm the accuracy of the pricing methods. Also some empirical applications are provided in the paper. (C) 2015 Elsevier B.V. All rights reserved.
A cumulant-based lattice algorithm for multichannel adaptive filtering is proposed in this paper. Proposed algorithm takes into account the advantages of higer-order statistics, that is, improvement of estimation accu...
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A cumulant-based lattice algorithm for multichannel adaptive filtering is proposed in this paper. Proposed algorithm takes into account the advantages of higer-order statistics, that is, improvement of estimation accuracy, blindness to colored Gaussian noise and the possibility to estimate the nonminimum-phase system etc. Without invoking the Instrumental Variable (IV) method as used in other papers [1], [2], the algorithm is derived directly from the recursive pseudo-inverse matrix. The behavior of the algorithm is illustrated by numerical examples.
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