Review on the Current Stochastic Numerical Methods for Econometric Analysis

Lewis N.K.Mambo; Rostin M.M.Mabela; Jean-Pierre B.Bosonga; Eugene M.Mbuyi

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Review on the Current Stochastic Numerical Methods for Econometric Analysis

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The main aim of this paper is to present and emphasize the contribution of stochastic numerical methods as must tools for the modern econometric modelisation. Indeed, the stochastic numerical methods play an important role in mathematical modelling and the econometric analysis because they model uncertainties that govern the real-world data. However these powerful tools are not well-known and understood by many economists and financial econometricians.

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来源
《美国计算数学期刊（英文）》 |2019年第4期|328-347|共20页
作者
Lewis N.K.Mambo; Rostin M.M.Mabela; Jean-Pierre B.Bosonga; Eugene M.Mbuyi;
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作者单位

Department of Economics;

University of Kinshasa;

Kinshasa;

Congo;

Central Bank of Congo;

Kinshasa;

Congo;

Department of Mathematics and Computer Sciences;

University of Kinshasa;

Kinshasa;

Congo;

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原文格式 PDF
正文语种 chi
中图分类数学分析;
关键词
Stochastic Differential Equations; The Euler-Maruyama Scheme; The Milstein Scheme; The Crank-Nicolson Scheme; Runge-Kutta Method; Ito Integrals; Econometric Analysis;

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Review on the Current Stochastic Numerical Methods for Econometric Analysis

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