Linear and non-linear (non-)forecastability of high-frequency exchange rates

This paper forecasts Daily Sterling exchange rate returns using various naive, linear and non-linear univariate time-series models. The accuracy of the forecasts is evaluated using mean squared error and sign prediction criteria. These show only a very modest improvement over forecasts generated by a random walk model. The Pesaran–Timmerman test and a comparison with forecasts generated artificially shows that even the best models have no evidence of market timing ability.

Gas exchange rates, plant height, yield components, and productivity of upland rice as affected by plant regulators

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Gas exchange rates at different vapor pressure deficits and water relations of 'Pera' sweet orange plants with citrus variegated chlorosis (CVC)

Net photosynthesis (A) and transpiration rates (E), stomatal conductance (g), water use efficiency (WUE), intrinsic water use efficiency (IWUE) and internal leaf CO2 concentration (C) in response to different vapor pressure deficit (1.2 and 2.5 kPa) were investigated in 'Pera' sweet orange plants affected by citrus variegated chlorosis (CVC), a disease caused by Xylella fastidiosa. All plants were well watered and leaf water potential (Pw) was also measured by the psychrometric technique. Results showed that healthy plants responded to higher vapor pressure deficit (VPD), lowering its net photosynthesis and transpiration rates, and stomatal conductance. However, diseased plants presented no clear response to VPD, showing lower A, E and g for both VPDs studied and very similar values to these variables in healthy plants at the highest VPD. Internal leaf CO2 concentration also decreased for healthy plants when under the highest VPD, and surprisingly, the same pattern of response was found in plants with CVC. These results, the lower Psi(w) and higher WUE values for diseased plants, indicated that this disease may cause stomatal dysfunction and affect the water resistance through xylem vessels, which ultimately may play some role in photosynthetic metabolism. (C) 2003 Elsevier B.V. B.V. All rights reserved.

Los tipos de cambio duales y el desarrollo económico = Dual exchange rates and economic development

Publicado separadamente en cada idioma

Formation of Exchange Rates on the Russian Market: Dynamics and Modelling

Galina Kovaleva. The Formation of the Exchange Rate on the Russian Market: Dynamics and Modelling. The Russian financial market is fast becoming one of the major sectors of the Russian economy. Assets have been increasing steadily, while new market segments and new financial market instruments have emerged. Kovaleva attempted to isolate the factors influencing exchange rates, determine patterns in the dynamic changes to the rouble/dollar exchange rate, construct models of the processes, and on the basis of these activities make forecasts. She studied the significance of economic indicators influencing the rouble/dollar exchange rate at different times, and developed multi-factor econometric models. In order to reveal the inner structure of the financial indicators and to work out ex-post forecasts for different time intervals, she carried out a series of calculations with the aim of constructing trend-cyclical (TC) and harmonic models, and Box and Jenkins models. She found that: 1. The Russian financial market is dependant on the rouble/dollar exchange rate. Its dynamics are formed under the influence of the short-term state treasury notes and government bonds markets, interbank loans, the rouble/DM exchange rate, the inflation rate, and the DM/dollar exchange rate. The exchange rate is influenced by sales on the Moscow Interbank Currency Exchange and the mechanism of those sales. 2. The TC model makes it possible to conduct an in-depth study of the structure of the processes and to make forecasts of the dynamic changes to currency indicators. 3. The Russian market is increasingly influenced by the world currency market and its prospects are of crucial interest for the world financial community.

Trade, Exchange Rates, and Macroeconomic Dynamics in East Asia: Why the Electronics Cycle Matters

Against the background of increasing regional trade and investment, there is growing interest in monetary and macroeconomic policy coordination in East Asia. Although there is a sizable literature on macroeconomic linkages among East Asian countries and the potential merit of policy coordination in the region, the existing studies tend to examine these issues exclusively in terms of macroeconomic variables and do not consider how these aggregate variables are influenced by one prominent feature of a number of East Asian economies: their heavy dependence on the electronics industry. Although active engagement in the global electronics industry has been a powerful growth engine for the Asian countries, it has also left their economies vulnerable to cyclical fluctuations in the world electronics market. As the cycle of the global electronics industry exerts profound impacts on the medium-term dynamics of the Asian economies, it is imperative to take an explicit account of its influence when studying the way in which the regional economies are linked to one another and how this relationship can be altered by a specific policy initiative. We illustrate the importance of this point by examining recent studies on: (1) trade competition between China andother Asian countries and the role of the Chinese renminbi therein; and (2) the effect offluctuations in the yen/dollar exchange rate on the regional economies.

A unified framework of trade in value added : physical, monetary, exchange rates, and GHG emissions

Koopman et al. (2014) developed a method to consistently decompose gross exports in value-added terms that accommodate infinite repercussions of international and inter-sector transactions. This provides a better understanding of trade in value added in global value chains than does the conventional gross exports method, which is affected by double-counting problems. However, the new framework is based on monetary input--output (IO) tables and cannot distinguish prices from quantities; thus, it is unable to consider financial adjustments through the exchange market. In this paper, we propose a framework based on a physical IO system, characterized by its linear programming equivalent that can clarify the various complexities relevant to the existing indicators and is proved to be consistent with Koopman's results when the physical decompositions are evaluated in monetary terms. While international monetary tables are typically described in current U.S. dollars, the physical framework can elucidate the impact of price adjustments through the exchange market. An iterative procedure to calculate the exchange rates is proposed, and we also show that the physical framework is also convenient for considering indicators associated with greenhouse gas (GHG) emissions.

The effect of OPEC oil pricing on output, prices, and exchange rates in the United States and other industrial countries /

Mode of access: Internet.

Forecasting exchange rates with linear and nonlinear models

In this paper, the exchange rate forecasting performance of neural network models are evaluated against the random walk, autoregressive moving average and generalised autoregressive conditional heteroskedasticity models. There are no guidelines available that can be used to choose the parameters of neural network models and therefore, the parameters are chosen according to what the researcher considers to be the best. Such an approach, however,implies that the risk of making bad decisions is extremely high, which could explain why in many studies, neural network models do not consistently perform better than their time series counterparts. In this paper, through extensive experimentation, the level of subjectivity in building neural network models is considerably reduced and therefore giving them a better chance of Forecasting exchange rates with linear and nonlinear models 415 performing well. The results show that in general, neural network models perform better than the traditionally used time series models in forecasting exchange rates.

Monetary models of exchange rates and sweep programs

Numerous studies find that monetary models of exchange rates cannot beat a random walk model. Such a finding, however, is not surprising given that such models are built upon money demand functions and traditional money demand functions appear to have broken down in many developed countries. In this article, we investigate whether using a more stable underlying money demand function results in improvements in forecasts of monetary models of exchange rates. More specifically, we use a sweep-adjusted measure of US monetary aggregate M1 which has been shown to have a more stable money demand function than the official M1 measure. The results suggest that the monetary models of exchange rates contain information about future movements of exchange rates, but the success of such models depends on the stability of money demand functions and the specifications of the models.