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Metropolis-Hastings prefetching algorithms

Strid, Ingvar (contributor) - 2008 - Rev. December 2, 2009

Prefetching is a simple and general method for single-chain parallelisation of the Metropolis-Hastings algorithm based … on the idea of evaluating the posterior in parallel and ahead of time. Improved Metropolis-Hastings prefetching … states of the chain and increase the efficiency of prefetching considerably. The optimal acceptance rate for the prefetching …

Persistent link: https://www.econbiz.de/10003779724

An Efficient Algorithm for the Calibration of Agent-Based Models Using Machine Learning

Zegadło, Piotr - 2020

A new algorithm for calibrating agent-based models is proposed, which employs a popular gradient boosting framework. Machine learning techniques are not used to develop a surrogate model, but rather assist in narrowing down the parameter space during the search for optimal parameters. Our...

Persistent link: https://www.econbiz.de/10012839291

The market resources method for solving dynamic optimization problems

Kabukçuoğlu, Ayşe; Martínez-García, Enrique - 2016 - This draft: June 16, 2016

We introduce the market resources method (MRM) for solving dynamic optimization problems. MRM extends Carroll’s (2006) endogenous grid point method (EGM) for problems with more than one control variable using policy function iteration. The MRM algorithm is simple to implement and provides...

Persistent link: https://www.econbiz.de/10011509578

Median as a Weighted Arithmetic Mean of All Sample Observations : Obtaining Weights by the Host-Parasite Co-Evolutionary Algorithm of Global Optimization

Mishra, Sudhanshu K. - 2013

This note is intended to demonstrate that median (a well-known measure of central tendency) is a weighted arithmetic mean of all sample observations and such (non-trivial) weights may be computed by an optimization method such as the host-parasite co-evolutionary algorithm

Persistent link: https://www.econbiz.de/10014037959

A review of heuristic optimization methods in econometrics

Gilli, Manfred; Winker, Peter - 2008

Estimation and modelling problems as they arise in many fields often turn out to be intractable by standard numerical methods. One way to deal with such a situation consists in simplifying models and procedures. However, the solutions to these simplified problems might not be satisfying. A...

Persistent link: https://www.econbiz.de/10003961503

Empirical Pricing Kernel Estimation Using a Functional Gradient Descent Algorithm Based on Splines

Meier, Pirmin - 2012

We propose a new methodology to estimate the empirical pricing kernel implied from option data. In contrast to most of the studies in the literature that use an indirect approach, i.e. first estimating the physical and risk-neutral densities and obtaining the pricing kernel in a second step, we...

Persistent link: https://www.econbiz.de/10013108080

Least Squares Estimation of Joint Production Functions By the Differential Evolution Method of Global Optimization

Mishra, Sudhanshu K. - 2007

In the economics of joint production one often distinguishes between the two cases: the one in which a firm produces multiple products each produced under separate production process, and the other "true joint production" where a number of outputs are produced from a single production process,...

Persistent link: https://www.econbiz.de/10014048371

Reducing Errors-in-Variables Bias in Linear Regression Using Compact Genetic Algorithms

Diyarbakirlioglu, Erkin; Satman, Mehmet Hakan - 2020

A new technique is devised to mitigate the errors-in-variables bias in linear regression. The procedure mimics a 2-stage least squares procedure where an auxiliary regression which generates a better behaved predictor variable is derived. The generated variable is then used as a substitute for...

Persistent link: https://www.econbiz.de/10014102272

Evolutionary Computational Approach in TAR Model Estimation

Parpinel, Francesca - 2012

The well-known SETAR model introduced by Tong belongs to the wide class of TAR models that may be specified in several different ways. Here we propose to consider the delay parameter as endogenous, that is we make it to depend on both the past value and the specific past regime of the series. In...

Persistent link: https://www.econbiz.de/10013111893

A data-driven explainable case-based reasoning approach for financial risk detection

Li, Wei; Paraschiv, Florentina; Sermpinis, Georgios - 2021

The rapid development of artificial intelligence methods contributes to their wide applications for forecasting various financial risks in recent years. This study introduces a novel explainable case-based reasoning (CBR) approach without a requirement of rich expertise in financial risk....

Persistent link: https://www.econbiz.de/10012584957

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