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Long Memory Modelling of Inflation with Stochastic Variance and Structural Breaks

Bos, Charles S.; Koopman, Siem Jan; Ooms, Marius - 2008

We investigate changes in the time series characteristics of postwar U.S. inflation. In a model-based analysis the conditional mean of inflation is specified by a long memory autoregressive fractionally integrated moving average process and the conditional variance is modelled by a stochastic...

Persistent link: https://www.econbiz.de/10014221102

Long memory modelling of inflation with stochastic variance and structural breaks

Bos, Charles S.; Koopman, Siem Jan; Ooms, Marius - 2007

Persistent link: https://www.econbiz.de/10011373822

Modelling Stochastic Volatility with Leverage and Jumps : A Simulated Maximum Likelihood Approach via Particle Filtering

Malik, Sheheryar; Pitt, Michael K. - 2011

In this paper we provide a unified methodology for conducting likelihood-based inference on the unknown parameters of a general class of discrete-time stochastic volatility (SV) models, characterized by both a leverage effect and jumps in returns. Given the nonlinear/non-Gaussian state-space...

Persistent link: https://www.econbiz.de/10014185810

Value Function Approximation or Stopping Time Approximation : A Comparison of Two Recent Numerical Methods for American Option Pricing using Simulation and Regression

Stentoft, Lars - 2012

In Longstaff and Schwartz (2001) a method for American option pricing using simulation and regression is suggested, and … since then the method has rapidly gained importance. However, the idea of using regression and simulation for American …

Persistent link: https://www.econbiz.de/10014212073

Stochastic Intrinsic Kriging for Simulation Metamodelling

Mehdad, Ehsan; Kleijnen, Jack P. C. - 2015

Kriging provides metamodels for deterministic and random simulation models. Actually, there are several types of … estimation of the trend in the input-output data of the underlying simulation model; this estimation deteriorates the Kriging … replications that varies with the input combination of the simulation model. To compare the performance of intrinsic Kriging and …

Persistent link: https://www.econbiz.de/10014142481

Stochastic Automatic Differentiation : Efficient Tapeless Implementation of Automatic Differentiation for Monte-Carlo Simulations

Fries, Christian P. - 2017

In this paper we present an efficient implementation of automatic differentiations of random variables (see 'https://ssrn.com/abstract=2995695' https://ssrn.com/abstract=2995695).Using this implementation can increase the speed of the calculation of the automatic differentiation and reduce the...

Persistent link: https://www.econbiz.de/10012950879

Markov Chain Monte Carlo Models, Gibbs Sampling, & Metropolis Algorithm for High-Dimensionality Complex Stochastic Problems

Malhotra, Yogesh - 2015

Markov chain Monte Carlo (MCMC) methods have an important role in solving high dimensionality stochastic problems characterized by computational complexity. Given their critical importance, there is need for network and security risk management research to relate the MCMC quantitative...

Persistent link: https://www.econbiz.de/10013029835

Stochastic Automatic Differentiation - AAD for Monte-Carlo Simulations - MVA Approximation Methods (Presentation Slides from the 14th Quant Finance Conference, Nice)

Fries, Christian P. - 2018

This first part of this presentation gives an introduction to stochastic automatic differentiation and its application.The second part of the presentation introduces a simple "static hedge" approximation for an SIMM based MVA and compares it with an exact solution (where the exact solution was...

Persistent link: https://www.econbiz.de/10012909792

Method of Iterated Integrals for Solution of Stochastic Integrals with Applications to Monte Carlo Simulation of Stochastic Differential Equations

Amin, Ahsan - 2018

integrand are given by some stochastic differential equation. We also propose numerical simulation of stochastic differential … integrals terms at the initial time of the simulation along with the solution of the stochastic integrals which is found in … terms of Hermite polynomials and variance of the integrals. We apply the method of iterated integrals to simulation of …

Persistent link: https://www.econbiz.de/10012925940

Stochastic household forecasts by coherent random shares predictions

Keilman, Nico; Duin, Coen van - 2014 - This version 14 April 2014

We compute a stochastic household forecast for the Netherlands by the random share method. Time series of shares of persons in nine household positions, broken down by sex and five-year age group for the years 1996-2010 are modelled by means of the Hyndman-Booth-Yasmeen product-ratio variant of...

Persistent link: https://www.econbiz.de/10010354141