Home  About us  Contact
 

Exchange Rate Data (exchange + rate_data)

Distribution by Scientific Domains
Business, Economics, Finance and Accounting75%

Selected Abstracts

Smooth Transition Models and Arbitrage Consistency

ECONOMICA, Issue 287 2005
David A. Peel
Slow adjustment of real exchange rate towards equilibrium in linear models has long puzzled researchers, stimulating the adoption of nonlinear models. The exponential smooth transition model has been particularly successful, providing faster adjustment speeds. This paper discusses some of its theoretical limitations, for example that expectations are adaptive. We propose a new nonlinear model conceptually superior to the ESTAR model since it is consistent with rational expectations. One of its advantages is that it can be solved and estimated by nonlinear least squares. Using monthly post-1973 real exchange rate data, we show that the model implies even faster speeds of adjustment. [source]

Predicting direction shifts on Canadian,US exchange rates with artificial neural networks

INTELLIGENT SYSTEMS IN ACCOUNTING, FINANCE & MANAGEMENT, Issue 2 2001
Jefferson T. Davis
The paper presents a variety of neural network models applied to Canadian,US exchange rate data. Networks such as backpropagation, modular, radial basis functions, linear vector quantization, fuzzy ARTMAP, and genetic reinforcement learning are examined. The purpose is to compare the performance of these networks for predicting direction (sign change) shifts in daily returns. For this classification problem, the neural nets proved superior to the naïve model, and most of the neural nets were slightly superior to the logistic model. Using multiple previous days' returns as inputs to train and test the backpropagation and logistic models resulted in no increased classification accuracy. The models were not able to detect a systematic affect of previous days' returns up to fifteen days prior to the prediction day that would increase model performance. Copyright © 2001 John Wiley & Sons, Ltd. [source]

Volatility dynamics and heterogeneous markets

INTERNATIONAL JOURNAL OF FINANCE & ECONOMICS, Issue 2 2006
David G. McMillan
Abstract Recent research has suggested that intra-day volatility may possess a component structure, resulting either from the arrival of heterogeneous information or the actions of heterogeneous market agents. This paper reports direct evidence for the existence of such components in S&P500 index and DM/$ exchange rate data. Estimation of a FIGARCH model supports the contention that volatility dynamics result from multiple sources. Using a HARCH conditional variance model which defines volatility components over differing time horizons, confirmatory evidence of heterogeneous components is reported, in which context the impact of high-frequency speculation and noise-trading are particularly apparent. Copyright © 2006 John Wiley & Sons, Ltd. [source]

Structure and dynamics of translation initiation factor aIF-1A from the archaeon Methanococcus jannaschii determined by NMR spectroscopy

PROTEIN SCIENCE, Issue 12 2001
Wei Li
Abstract Translation initiation factor 1A (aIF-1A) from the archaeon Methanococcus jannaschii was expressed in Escherichia coli, purified, and characterized in terms of its structure and dynamics using multidimensional NMR methods. The protein was found to be a member of the OB-fold family of RNA-associated proteins, containing a barrel of five beta-strands, a feature that is shared with the homologous eukaryotic translation initiation factor 1A (eIF-1A), as well as the prokaryotic translation initiation factor IF1. External to the , barrel, aIF-1A contains an ,-helix at its C-terminal and a flexible loop at its N-terminal, features that are qualitatively similar to those found in eIF-1A, but not present in prokaryotic IF1. The structural model of aIF-1A, when used in combination with primary sequence information for aIF-1A in divergent species, permitted the most-conserved residues on the protein surface to be identified, including the most likely candidates for direct interaction with the 16S ribosomal RNA and other components of the translational apparatus. Several of the conserved surface residues appear to be unique to the archaea. Nitrogen-15 relaxation and amide exchange rate data were used to characterize the internal motions within aIF-1A, providing evidence that the protein surfaces that are most likely to participate in intermolecular interactions are relatively flexible. A model is proposed, suggesting some specific interactions that may occur between aIF-1A and the small subunit of the archaeal ribosome. [source]