Detecting and Measuring Financial cycles in Heterogeneous Agents Models: an Empirical Analysis

IF 0.7 4区 数学 Q4 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Advances in Complex Systems Pub Date : 2022-01-01 DOI:10.1142/S0219525922400021
Filippo Gusella
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引用次数: 1

Abstract

This paper proposes a macroeconometric analysis to depict and measure possible nancial cycles that emerge due to the dynamic interaction between heterogeneous market participants. We consider 2-type heterogeneous speculative agents: Trend followers tend to follow the price trend while contrarians go against the wind. As agents' beliefs are unobserved variables, we construct a state-space model where heuristics are considered as unobserved state components and from which the conditions for endogenous cycles can be mathematically derived and empirically tested. Further, we speci cally measure the length of endogenous nancial cycles. The model is estimated using the equity price index for the 196
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异质性主体模型中金融周期的检测与度量:一个实证分析
本文提出了一种宏观计量经济学分析来描述和衡量由于异质市场参与者之间的动态相互作用而出现的可能的金融周期。我们考虑两类异质投机主体:趋势跟随者倾向于跟随价格趋势,而逆向投资者则逆风而行。由于代理的信念是不可观察的变量,我们构建了一个状态空间模型,其中启发式被认为是不可观察的状态成分,并且可以从数学上推导出内源性周期的条件并进行经验检验。此外,我们特别测量了内生金融周期的长度。该模型是用1996年的股票价格指数来估计的
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来源期刊
Advances in Complex Systems
Advances in Complex Systems 综合性期刊-数学跨学科应用
CiteScore
1.40
自引率
0.00%
发文量
121
审稿时长
6-12 weeks
期刊介绍: Advances in Complex Systems aims to provide a unique medium of communication for multidisciplinary approaches, either empirical or theoretical, to the study of complex systems. The latter are seen as systems comprised of multiple interacting components, or agents. Nonlinear feedback processes, stochastic influences, specific conditions for the supply of energy, matter, or information may lead to the emergence of new system qualities on the macroscopic scale that cannot be reduced to the dynamics of the agents. Quantitative approaches to the dynamics of complex systems have to consider a broad range of concepts, from analytical tools, statistical methods and computer simulations to distributed problem solving, learning and adaptation. This is an interdisciplinary enterprise.
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