Fixing Exchange Rates: A Virtual Quest for Fundamentals

Flood, Robert P.; Rose, A.

doi:10.3386/w4503

Cited by 192 publications

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“…3 Within this setting the stabilizing effect of the target zone on exchange rates results from tying down the hands of future monetary policy. However, as pointed out by Krugman and Miller (1993), the efficient market assumption is particularly misleading as policy-makers introduced target zone arrangements precisely because empirical research convinced them that exchange rates exhibit persistent misalignments (Rogoff, 1996) and excess volatility (Flood and Rose, 1995). In order to overcome this contradiction Sarno and Taylor (2002) suggest the analysis of target zone with the allowance for heterogeneous agents.…”

Section: Introductionmentioning

confidence: 99%

Exchange Rate Dynamics in a Target Zone - A Heterogeneous Expectations Approach

Bauer

Reitz

2008

SSRN Journal

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The target zone model of Krugman (1991) has failed empirically. In this paper, we develop a model of the exchange rate with heterogeneous agents in a free floating and a target zone regime. We show that this simple model mimics the empirical puzzles of exchange rates: excessive volatility, fat tails, volatility clustering, and disconnection from the fundamentals. In addition, the target zone regime replicates a reduced nominal volatility for the same level of fundamental volatility as in the free floating regime and the distribution of the exchange rate within the band is hump-shaped.JEL Code: F31, F41.

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Section: Introductionmentioning

confidence: 99%

Exchange Rate Dynamics in a Target Zone - A Heterogeneous Expectations Approach

Bauer

Reitz

2008

SSRN Journal

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“…In fact, the volatility of macroeconomic fundamentals such as money and output do not change much across currency regimes (Flood and Rose, 1995). Therefore, Flood and Rose (1995, p. 5) suggest that macroeconomic fundamentals alone are unable to explain exchange rate volatility: 3 3 "Exchange rate volatility" and "exchange rate stability"are used synonymously by Flood and Rose (1995). "Intuitively, if exchange rate stability varies across regimes without corresponding variation in macroeconomic volatility, then macroeconomic variables will be unable to explain much exchange rate volatility".…”

Section: Discussionmentioning

confidence: 99%

Chartism and exchange rate volatility

Bask

2007

Int. J Fin Econ

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The purpose of this paper is to implement theoretically, the observation that the relative importance of fundamental versus technical analysis in the foreign exchange market depends on the time horizon in currency trade. For shorter time horizons, more weight is placed on technical analysis, while more weight is placed on fundamental analysis for longer horizons. The theoretical framework is the Dornbusch (1976) overshooting model, where moving averages is the technical trading technique used by the chartists. The perfect foresight path near long-run equilibrium is derived, and it is shown that the magnitude of exchange rate overshooting is larger than in the Dornbusch (1976) model. Specifically, the extent of overshooting depends inversely on the time horizon in currency trade. How changes in the model's structural parameters endogenously affect this time horizon and the magnitude of exchange rate overshooting along the perfect foresight path are also derived. JEL Classification: F31, F41

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“…linear or nonlinear is also a matter for investigation. Ever since the influential work of Meese and Rogoff (1983) in which they examined the failure of some linear exchange rate models, several more recent studies have provided further evidence of the empirical failure of the linear models (Flood and Rose, 1995;Rose, 1996). The theoretical extension of the linear exchange rate framework to nonlinear models has been growing in the literature.…”

Section: Introductionmentioning

confidence: 99%

The nonlinear dynamic relationship of exchange rates: Parametric and nonparametric causality testing

Bekiros

Diks

2008

Journal of Macroeconomics

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The present study investigates the long-term linear and nonlinear causal linkages among six currencies, namely EUR/USD, GBP/USD, USD/JPY, USD/CHF, AUD/USD and USD/CAD. The prime motivation for choosing these exchange rates comes from the fact that they are the most liquid and widely traded, covering about 90% of total FX trading worldwide. The data spans two periods (PI: 3/20/1991 -3/20/1997, PII: 3/20/2003 -3/20/2007) before and after the structural break of the Asian financial crisis, which set a platform for departure for causality testing. We apply a new nonparametric test for Granger non-causality by Diks and Panchenko (2005, 2006) as well as the conventional linear Granger test on the return time series. To ensure that any causality is strictly nonlinear in nature, we also examine the nonlinear causal relationships of pairwise VAR filtered residuals as well as in a six-variate formulation. We find remaining significant biand uni-directional causal nonlinear relationships in the return series. Finally, we investigate the hypothesis of nonlinear non-causality after controlling for conditional heteroskedasticity in the data using a GARCH-BEKK model. Our approach allows the entire variance-covariance structure of the currency interrelationship to be incorporated in order to explicitly capture the volatility spillover mechanism. Whilst the nonparametric test statistics are smaller in some cases, significant nonlinear causal linkages persisted even after GARCH filtering during both the pre-and post-Asian crisis period. This indicates that currency returns may exhibit asymmetries and statistically significant higher-order moments.JEL classification: C14; C51; F31

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Fixing Exchange Rates: A Virtual Quest for Fundamentals

Cited by 192 publications

References 0 publications

Exchange Rate Dynamics in a Target Zone - A Heterogeneous Expectations Approach

Exchange Rate Dynamics in a Target Zone - A Heterogeneous Expectations Approach

Chartism and exchange rate volatility

The nonlinear dynamic relationship of exchange rates: Parametric and nonparametric causality testing

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