Econometric analysis of microscopic simulation models

Y. Li, A.C.D. Donkers, B. Melenberg

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Microscopic simulation models are often evaluated based on visual inspection of the results. This paper presents formal econometric techniques to compare microscopic simulation (MS) models with real-life data. A related result is a methodology to compare different MS models with each other. For this purpose, possible parameters of interest, such as mean returns, or autocorrelation patterns, are classified and characterized. For each class of characteristics, the appropriate techniques are presented. We illustrate the methodology by comparing the MS model developed by He and Li [J. Econ. Dynam. Control, 2007, 31, 3396–3426, Quant. Finance, 2008, 8, 59–79] with actual data.
Original languageEnglish
Pages (from-to)1187-1201
JournalQuantitative Finance
Volume10
Issue number10
Publication statusPublished - 2010

Fingerprint

Simulation model
Econometric analysis
Methodology
Finance
Econometrics
Inspection
Autocorrelation

Cite this

Li, Y. ; Donkers, A.C.D. ; Melenberg, B. / Econometric analysis of microscopic simulation models. In: Quantitative Finance. 2010 ; Vol. 10, No. 10. pp. 1187-1201.
@article{a7a6eda5077f4269825a62a15bc35fd4,
title = "Econometric analysis of microscopic simulation models",
abstract = "Microscopic simulation models are often evaluated based on visual inspection of the results. This paper presents formal econometric techniques to compare microscopic simulation (MS) models with real-life data. A related result is a methodology to compare different MS models with each other. For this purpose, possible parameters of interest, such as mean returns, or autocorrelation patterns, are classified and characterized. For each class of characteristics, the appropriate techniques are presented. We illustrate the methodology by comparing the MS model developed by He and Li [J. Econ. Dynam. Control, 2007, 31, 3396–3426, Quant. Finance, 2008, 8, 59–79] with actual data.",
author = "Y. Li and A.C.D. Donkers and B. Melenberg",
note = "Appeared earlier as CentER DP 2006-99",
year = "2010",
language = "English",
volume = "10",
pages = "1187--1201",
journal = "Quantitative Finance",
issn = "1469-7688",
publisher = "Routledge",
number = "10",

}

Li, Y, Donkers, ACD & Melenberg, B 2010, 'Econometric analysis of microscopic simulation models', Quantitative Finance, vol. 10, no. 10, pp. 1187-1201.

Econometric analysis of microscopic simulation models. / Li, Y.; Donkers, A.C.D.; Melenberg, B.

In: Quantitative Finance, Vol. 10, No. 10, 2010, p. 1187-1201.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Econometric analysis of microscopic simulation models

AU - Li, Y.

AU - Donkers, A.C.D.

AU - Melenberg, B.

N1 - Appeared earlier as CentER DP 2006-99

PY - 2010

Y1 - 2010

N2 - Microscopic simulation models are often evaluated based on visual inspection of the results. This paper presents formal econometric techniques to compare microscopic simulation (MS) models with real-life data. A related result is a methodology to compare different MS models with each other. For this purpose, possible parameters of interest, such as mean returns, or autocorrelation patterns, are classified and characterized. For each class of characteristics, the appropriate techniques are presented. We illustrate the methodology by comparing the MS model developed by He and Li [J. Econ. Dynam. Control, 2007, 31, 3396–3426, Quant. Finance, 2008, 8, 59–79] with actual data.

AB - Microscopic simulation models are often evaluated based on visual inspection of the results. This paper presents formal econometric techniques to compare microscopic simulation (MS) models with real-life data. A related result is a methodology to compare different MS models with each other. For this purpose, possible parameters of interest, such as mean returns, or autocorrelation patterns, are classified and characterized. For each class of characteristics, the appropriate techniques are presented. We illustrate the methodology by comparing the MS model developed by He and Li [J. Econ. Dynam. Control, 2007, 31, 3396–3426, Quant. Finance, 2008, 8, 59–79] with actual data.

M3 - Article

VL - 10

SP - 1187

EP - 1201

JO - Quantitative Finance

JF - Quantitative Finance

SN - 1469-7688

IS - 10

ER -