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CapMod : A Simulated Society to Evaluate Empirical Estimators of Capabilities
Chávez-Juárez, Florian; Krishnakumar, Jaya - 2019
This article introduces an innovative approach to the validation of empirical methods aiming at estimating capabilities. Validating these empirical methods is difficult because capabilities are not directly observable. We propose a computational model to generate data from a simulated society,...
Persistent link: https://www.econbiz.de/10014108528
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Exact Moment Simulation Using Random Orthogonal Matrices
Alexander, Carol; Ledermann, Walter; Ledermann, Dan - 2010
methodology is thus termed "ROM simulation''. We discuss certain classes of random orthogonal matrices and show how each class … kurtosis. A new class of rectangular orthogonal matrices is fundamental to the methodology, and these "L-matrices'' can be … produces samples with different characteristics. ROM simulation has applications to many problems that are resolved using …
Persistent link: https://www.econbiz.de/10014204404
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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
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Chapter 9. Analysis of Numerical Errors
Peralta-Alva, Adrian; Santos, Manuel S. - In: Handbook of computational economics : volume 3, (pp. 517-556). 2014
This paper provides a general framework for the quantitative analysis of stochastic dynamic models. We review the convergence properties of some numerical algorithms and available methods to bound approximation errors. We then address the convergence and accuracy properties of the simulated...
Persistent link: https://www.econbiz.de/10014025713
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Uncertainty of Multiple Period Risk Measures
Lönnbark, Carl - 2009
simulation experiment we conclude that among the studied analytical approaches the one based on approximating the distribution of … the multiple period shocks by a skew-t was the best. It was almost as good as the simulation based alternative. We also …
Persistent link: https://www.econbiz.de/10013155481
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Simulated ML estimation of financial agent-based models
Baruník, Jozef; Kukačka, Jiří - 2016
This paper proposes computational framework for empirical estimation of Financial Agent-Based Models (FABMs) that does not rely upon restrictive theoretical assumptions. We customise a recent methodology of the Non-Parametric Simulated Maximum Likelihood Estimator (NPSMLE) based on kernel...
Persistent link: https://www.econbiz.de/10011448663
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Tail distribution of the maximum of correlated Gaussian random variables
Botev, Zdravko I.; Mandjes, Michel; Ridder, Ad - 2015
In this article we consider the efficient estimation of the tail distribution of the maximum of correlated normal random variables. We show that the currently recommended Monte Carlo estimator has difficulties in quantifying its precision, because its sample variance estimator is an inefficient...
Persistent link: https://www.econbiz.de/10011431354
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A flexible state-space model with lagged states and lagged dependent variables : simulation smoothing
Hauber, Philipp; Schumacher, Christian; Zhang, Jiachun - 2019
We provide a simulation smoother to a exible state-space model with lagged states and lagged dependent variables. Qian … efficient simulation smoother, which relies on mean corrections for unconditional vectors. When applied to a factor model, the … proposed simulation smoother for the states is efficient compared to other state-space models without lagged states and …
Persistent link: https://www.econbiz.de/10012000564
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Validation of agent-based models in economics and finance
Fagiolo, Giorgio; Guerini, Mattia; Lamperti, Francesco; … - 2017
Since the influential survey by Windrum et al. (2007), research on empirical validation of agent-based models in economics has made substantial advances, thanks to a constant flow of high-quality contributions. This Chapter attempts to take stock of such recent literature to offer an updated...
Persistent link: https://www.econbiz.de/10011729421
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Simulated Likelihood Estimators for Discretely Observed Jump-Diffusions
Giesecke, Kay - 2019
This paper develops an unbiased Monte Carlo approximation to the transition density of a jump-diffusion process with state-dependent drift, volatility, jump intensity, and jump magnitude. The approximation is used to construct a likelihood estimator of the parameters of a jump-diffusion observed...
Persistent link: https://www.econbiz.de/10012904646