2010
DOI: 10.1016/j.jimonfin.2010.05.007
|View full text |Cite
|
Sign up to set email alerts
|

Heterogeneity of agents and exchange rate dynamics: Evidence from the EMS

Abstract: We develop and estimate a dynamic heterogeneous agent model for the EMS period. Our empirical results suggest that the existence of heterogeneous interacting agents is indeed a possible explanation for the dynamics of exchange rates during the EMS; we find strong evidence in favor of our model using in-and out-of-sample tests. Moreover, we show that the heterogeneous agent model outperforms the random walk in out-of-sample forecasting in all country/period combinations. Finally, we study the dynamic limit prop… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

1
41
0

Year Published

2014
2014
2019
2019

Publication Types

Select...
6
3

Relationship

0
9

Authors

Journals

citations
Cited by 76 publications
(42 citation statements)
references
References 51 publications
1
41
0
Order By: Relevance
“…Boswijk et al (2007) estimate a version of the Hommes (1997, 1998) model directly for S&P 500 data using nonlinear least squares and Reitz (2003, 2005) and Reitz and Westerhoff (2007) use the STAR-GARCH model introduced by Lundbergh and Teräsvirta (1998) to estimate various models of chartists and fundamentalists for daily exchange rate data, the US corn market, and various other commodities markets, respectively. More recently, Cornea et al (2012) investigate behavioral heterogeneity in US inflation rate data using nonlinear least squares and de Jong et al (2010) estimate a HAM for the exchange-rate dynamics of the European Monetary System (EMS) using quasi-maximum likelihood techniques. Similar likelihood techniques are also employed in Kouwenberg and Zwinkels (2010) to investigate the 5 behaviour of the US housing market over the last 50 years and in ter Ellen and Zwinkels (2010) when considering oil price dynamics.…”
Section: Related Literaturementioning
confidence: 99%
“…Boswijk et al (2007) estimate a version of the Hommes (1997, 1998) model directly for S&P 500 data using nonlinear least squares and Reitz (2003, 2005) and Reitz and Westerhoff (2007) use the STAR-GARCH model introduced by Lundbergh and Teräsvirta (1998) to estimate various models of chartists and fundamentalists for daily exchange rate data, the US corn market, and various other commodities markets, respectively. More recently, Cornea et al (2012) investigate behavioral heterogeneity in US inflation rate data using nonlinear least squares and de Jong et al (2010) estimate a HAM for the exchange-rate dynamics of the European Monetary System (EMS) using quasi-maximum likelihood techniques. Similar likelihood techniques are also employed in Kouwenberg and Zwinkels (2010) to investigate the 5 behaviour of the US housing market over the last 50 years and in ter Ellen and Zwinkels (2010) when considering oil price dynamics.…”
Section: Related Literaturementioning
confidence: 99%
“…Frijns et al (2010) verify that traders with di¤erent beliefs about volatility are active in option market. Manzan and Westerho¤ (2007) and De Jong et al (2010) …nd the existence of heterogeneous traders in foreign exchange markets. Lux (2012) uses agent-based model to estimate the opinion formation of German investors.…”
Section: Introductionmentioning
confidence: 99%
“…When the past appreciation or depreciation of the exchange rate is larger than the threshold value, their behaviour becomes stabilising. De Jong et al (2010) find evidence of stabilising behaviour of all types of agents for EMS rates, a result they assign to the investors' trust in the monetary authorities.…”
Section: Foreign Exchange Marketmentioning
confidence: 84%
“…The form of the model we show here is mostly related to some of our own applications of HAM (e.g. De Jong et al, 2010;ter Ellen and Zwinkels, 2010;Chiarella et al, 2014), which are largely based on the functional form from Hommes (1997, 1998) and Boswijk et al (2007).…”
Section: An Examplementioning
confidence: 99%