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FAST ORTHOGONAL TRANSFORMS FOR PRICING DERIVATIVES WITH QUASIMONTE CARLO
"... There are a number of situations where, when computing prices of financial derivatives using quasiMonte Carlo (QMC), it turns out to be beneficial to apply an orthogonal transform to the standard normal input variables. Sometimes those transforms can be computed in time O(nlog(n)) for problems depe ..."
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There are a number of situations where, when computing prices of financial derivatives using quasiMonte Carlo (QMC), it turns out to be beneficial to apply an orthogonal transform to the standard normal input variables. Sometimes those transforms can be computed in time O(nlog(n)) for problems
Sequential data assimilation with a nonlinear quasigeostrophic model using Monte Carlo methods to forecast error statistics
 J. Geophys. Res
, 1994
"... . A new sequential data assimilation method is discussed. It is based on forecasting the error statistics using Monte Carlo methods, a better alternative than solving the traditional and computationally extremely demanding approximate error covariance equation used in the extended Kalman filter. The ..."
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Cited by 782 (22 self)
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. A new sequential data assimilation method is discussed. It is based on forecasting the error statistics using Monte Carlo methods, a better alternative than solving the traditional and computationally extremely demanding approximate error covariance equation used in the extended Kalman filter
QUASIMONTE CARLO METHODS IN FINANCE
"... We review the basic principles of QuasiMonte Carlo (QMC) methods, the randomizations that turn them into variancereduction techniques, and the main classes of constructions underlying their implementations: lattice rules, digital nets, and permutations in different bases. QMC methods are designed t ..."
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We review the basic principles of QuasiMonte Carlo (QMC) methods, the randomizations that turn them into variancereduction techniques, and the main classes of constructions underlying their implementations: lattice rules, digital nets, and permutations in different bases. QMC methods are designed
Recent Advances In Randomized QuasiMonte Carlo Methods
"... We survey some of the recent developments on quasiMonte Carlo (QMC) methods, which, in their basic form, are a deterministic counterpart to the Monte Carlo (MC) method. Our main focus is the applicability of these methods to practical problems that involve the estimation of a highdimensional inte ..."
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Cited by 78 (15 self)
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We survey some of the recent developments on quasiMonte Carlo (QMC) methods, which, in their basic form, are a deterministic counterpart to the Monte Carlo (MC) method. Our main focus is the applicability of these methods to practical problems that involve the estimation of a high
Implementing QuasiMonte Carlo Simulations with Linear Transformations
 Computational Management Science
, 2008
"... Pricing exotic multiasset pathdependent options requires extensive Monte Carlo simulations. In the recent years the interest to the Quasimonte Carlo technique has been renewed and several results have been proposed in order to improve its efficiency with the notion of effective dimension. To this ..."
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Cited by 3 (2 self)
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the linear transformation decomposition relying on a fast ad hoc QR decomposition that considerably reduces the computational burden. This setting makes the linear transformation method even more convenient from the computational point of view. We implement a highdimensional (2500) QuasiMonte Carlo
Sequential quasiMonte Carlo
, 2014
"... We develop a new class of algorithms, SQMC (Sequential QuasiMonte Carlo), as a variant of SMC (Sequential Monte Carlo) based on lowdiscrepancy point sets. The complexity of SQMC is O(N logN), where N is the number of simulations at each iteration, and its error rate is smaller than the Monte Carlo ..."
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Cited by 3 (2 self)
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We develop a new class of algorithms, SQMC (Sequential QuasiMonte Carlo), as a variant of SMC (Sequential Monte Carlo) based on lowdiscrepancy point sets. The complexity of SQMC is O(N logN), where N is the number of simulations at each iteration, and its error rate is smaller than the Monte
FAST VOLUME RENDERING USING A SHEARWARP FACTORIZATION OF THE VIEWING TRANSFORMATION
, 1995
"... Volume rendering is a technique for visualizing 3D arrays of sampled data. It has applications in areas such as medical imaging and scientific visualization, but its use has been limited by its high computational expense. Early implementations of volume rendering used bruteforce techniques that req ..."
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Cited by 541 (2 self)
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that require on the order of 100 seconds to render typical data sets on a workstation. Algorithms with optimizations that exploit coherence in the data have reduced rendering times to the range of ten seconds but are still not fast enough for interactive visualization applications. In this thesis we present a
Automobile prices in market equilibrium
 Econometrica
, 1995
"... Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at ..."
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Cited by 510 (18 self)
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Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at
Control variates for quasiMonte Carlo
, 2003
"... QuasiMonte Carlo (QMC) methods have begun to displace ordinary Monte Carlo (MC) methods in many practical problems. It is natural and obvious to combine QMC methods with traditional variance reduction techniques used in MC sampling, such as control variates. There can, ..."
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Cited by 11 (3 self)
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QuasiMonte Carlo (QMC) methods have begun to displace ordinary Monte Carlo (MC) methods in many practical problems. It is natural and obvious to combine QMC methods with traditional variance reduction techniques used in MC sampling, such as control variates. There can,
QuasiMonte Carlo Radiosity
, 1996
"... The problem of global illumination in computer graphics is described by a second kind Fredholm integral equation. Due to the complexity of this equation, Monte Carlo methods provide an interesting tool for approximating solutions to this transport equation. For the case of the radiosity equation, w ..."
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Cited by 40 (2 self)
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The problem of global illumination in computer graphics is described by a second kind Fredholm integral equation. Due to the complexity of this equation, Monte Carlo methods provide an interesting tool for approximating solutions to this transport equation. For the case of the radiosity equation
Results 1  10
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