Počet záznamů: 1
Network Theory and Agent-Based Modeling in Economics and Finance
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SYSNO ASEP 0510031 Druh ASEP M - Kapitola v monografii Zařazení RIV C - Kapitola v knize Název Simulated maximum likelihood estimation of agent-based models in economics and finance Tvůrce(i) Kukačka, Jiří (UTIA-B) RID, ORCID Celkový počet autorů 1 Zdroj.dok. Network Theory and Agent-Based Modeling in Economics and Finance. - Singapore : Springer, 2019 / Chakrabarti A. S. ; Pichl L. ; Kaizoji T. - ISBN 978-981-13-8318-2 Rozsah stran s. 203-226 Poč.str. 24 s. Poč.str.knihy 458 Forma vydání Tištěná - P Jazyk dok. eng - angličtina Země vyd. SG - Singapur Klíč. slova simulation-based framework ; kernel methods ; economic models Vědní obor RIV AH - Ekonomie Obor OECD Finance CEP GJ17-12386Y GA ČR - Grantová agentura ČR Institucionální podpora UTIA-B - RVO:67985556 DOI 10.1007/978-981-13-8319-9_10 Anotace This chapter presents a general simulation-based framework for estimation of agent-based models in economics and finance based on kernel methods. After discussing the distinguishing features between empirical estimation and calibration of economic models, the simulated maximum likelihood estimator is validated for utilization in agent-based econometrics. As the main advantage, the method allows for estimation of nonlinear models for which the analytical representation of the objective function does not exist. We test the properties and performance of the estimator in combination with the seminal Brock and Hommes (J Econ Dyn Control 22:1235–1274, 1998) asset pricing model, where the dynamics are governed by switching of agents between trading strategies based on the discrete choice approach. We also provide links to how the estimation method can be extended to multivariate macroeconomic optimization problems. Using simulation analysis, we show that the estimator consistently recovers the pseudo-true parameters with high estimation precision. We further study the impact of agents' memory on the estimation performance and show that while memory generally deteriorates the precision, the main properties of the estimator remain unaffected. Pracoviště Ústav teorie informace a automatizace Kontakt Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Rok sběru 2020
Počet záznamů: 1