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We reassess exchange rate prediction using a wider set of models that have been proposed in the last decade. The performance of these models is compared against two reference specifications-purchasing power parity and the sticky-price monetary model. The models are estimated in first-difference...
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Using exchange rate data on five currencies vis-à-vis the US dollar, this paper examines the in-sample and out-of-sample performance of exchange rate equations derived from alternative empirical and optimal interest rate rules. These rules could have either homogeneous or heterogeneous response...
Persistent link: https://www.econbiz.de/10009407674
Previous assessments of nominal exchange rate determination have focused upon a narrow set of models typically of the 1970 s vintage, including monetary and portfolio balance models. In this paper we re-assess the in-sample fit and out-of-sample prediction of a wider set of models that have been...
Persistent link: https://www.econbiz.de/10011507659
Previous assessments of forecasting performance of exchange rate models have focused upon a narrow set of models typically of the 1970's vintage. The canonical papers in this literature are by Meese and Rogoff (1983, 1988), who examined monetary and portfolio balance models. Succeeding works by...
Persistent link: https://www.econbiz.de/10011521412
Previous assessments of nominal exchange rate determination have focused upon a narrow set of models typically of the 1970's vintage, including monetary and portfolio balance models. In this paper we re-assess the in-sample fit and out-of-sample prediction of a wider set of models that have been...
Persistent link: https://www.econbiz.de/10011521440
We observe that daily highs and lows of stock prices do not diverge over time and, hence, adopt the cointegration concept and the related vector error correction model (VECM) to model the daily high, the daily low, and the associated daily range data. The in-sample results attest the importance...
Persistent link: https://www.econbiz.de/10003749656
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