Search Results - subject:"importance sampling."

Parallelization experience with four canonical econometric models using ParMitISEM

Baştürk, Nalan; Grassi, Stefano; Hoogerheide, Lennart; … - In: Econometrics : open access journal 4 (2016) 1, pp. 1-20

candidate density in Importance Sampling or Metropolis Hastings methods for Bayesian inference on model parameters and …

Persistent link: https://www.econbiz.de/10011504818

Evolutionary sequential Monte Carlo samplers for change-point models

Dufays, Arnaud - In: Econometrics : open access journal 4 (2016) 1, pp. 1-33

Sequential Monte Carlo (SMC) methods are widely used for non-linear filtering purposes. However, the SMC scope encompasses wider applications such as estimating static model parameters so much that it is becoming a serious alternative to Markov-Chain Monte-Carlo (MCMC) methods. Not only do SMC...

Persistent link: https://www.econbiz.de/10011504888

Parallelization experience with four canonical econometric models using ParMitISEM

Basturk, Nalan; Grassi, Stefano; Hoogerheide, Lennart; … - 2016

density is required. The approximation can be used as a candidate density in Importance Sampling or Metropolis Hastings …

Persistent link: https://www.econbiz.de/10011441581

Ruin probabilities with dependence on the number of claims within a fixed time window

Constantinescu, Corina; Dai, Suhang; Ni, Weihong; … - In: Risks : open access journal 4 (2016) 2, pp. 1-23

-form formulae. Additionally, we employ the importance sampling simulations to derive ruin probabilities, which further permit an in …

Persistent link: https://www.econbiz.de/10011507555

Risk neutral reformulation approach to risk averse stochastic programming

Liu, Rui Peng; Shapiro, Alexander - In: European journal of operational research : EJOR 286 (2020) 1, pp. 21-31

Persistent link: https://www.econbiz.de/10012239878

An effective hybrid variance reduction method for pricing the Asian options and its variants

Lu, King-Jeng; Liang, Chiung-Ju; Hsieh, Ming-Hua; Lee, … - In: The North American journal of economics and finance : a … 51 (2020), pp. 1-7

Persistent link: https://www.econbiz.de/10012659091

Partially censored posterior for robust and efficient risk evaluation

Borowska, Agnieszka; Hoogerheide, Lennart; Koopman, Siem Jan - In: Journal of econometrics 217 (2020) 2, pp. 335-355

Persistent link: https://www.econbiz.de/10012482776

The R-package MitISEM: Efficient and Robust Simulation Procedures for Bayesian Inference

Basturk, Nalan; Grassi, Stefano; Hoogerheide, Lennart; … - 2015

This paper presents the R-package <B>MitISEM</B> (mixture of <I>t</I> by importance sampling weighted expectation … where each step of the optimization procedure is weighted using importance sampling. In the second stage this mixture … density is a candidate density for efficient and robust application of importance sampling or the Metropolis-Hastings (MH …

Persistent link: https://www.econbiz.de/10011288392

Intraday Stochastic Volatility in Discrete Price Changes: the Dynamic Skellam Model

Koopman, Siem Jan; Lit, Rutger; Lucas, Andre - 2015

We introduce a dynamic Skellam model that measures stochastic volatility from high-frequency tick-by-tick discrete stock price changes. The likelihood function for our model is analytically intractable and requires Monte Carlo integration methods for its numerical evaluation. The proposed...

Persistent link: https://www.econbiz.de/10011403534

Tail Distribution of the Maximum of Correlated Gaussian Random Variables

Botev, Zdravko; Mandjes, Michel; Ridder, Ad - 2015

completely new sequential importance sampling estimator of the desired tail probability. Numerical experiments suggest that the … sequential importance sampling estimator can be significantly more efficient than its competitor. …

Persistent link: https://www.econbiz.de/10011451510