947 resultados para exchange rates


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This paper builds upon previous research on currency bands, and provides a model for the Colombian peso. Stochastic differential equations are combined with information related to the Colombian currency band to estimate competing models of the behaviour of the Colombian peso within the limits of the currency band. The resulting moments of the density function for the simulated returns describe adequately most of the characteristics of the sample returns data. The factor included to account for the intra-marginal intervention performed to drive the rate towards the Central Parity accounts only for 6.5% of the daily change, which supports the argument that intervention, if performed by the Central Bank, it is not directed to push the currency towards the limits. Moreover, the credibility of the Colombian Central Bank, Banco de la República’s ability to defend the band seems low.

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We consider the forecasting performance of two SETAR exchange rate models proposed by Kräger and Kugler [J. Int. Money Fin. 12 (1993) 195]. Assuming that the models are good approximations to the data generating process, we show that whether the non-linearities inherent in the data can be exploited to forecast better than a random walk depends on both how forecast accuracy is assessed and on the ‘state of nature’. Evaluation based on traditional measures, such as (root) mean squared forecast errors, may mask the superiority of the non-linear models. Generalized impulse response functions are also calculated as a means of portraying the asymmetric response to shocks implied by such models.

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This paper proposes two new tests for linear and nonlinear lead/lag relationships between time series based on the concepts of cross-correlations and cross-bicorrelations, respectively. The tests are then applied to a set of Sterling-denominated exchange rates. Our analysis indicates that there existed periods during the post-Bretton Woods era where the temporal relationship between different exchange rates was strong, although these periods have become less frequent over the past 20 years. In particular, our results demonstrate the episodic nature of the nonlinearity, and have implications for the speed of flow of information between financial series. The method generalises recently proposed tests for nonlinearity to the multivariate context.

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We examine a method recently proposed by Hinich and Patterson (mimeo, University of Texas at Austin, 1995) for testing the validity of specifying a GARCH error structure for financial time series data in the context of a set of ten daily Sterling exchange rates. The results demonstrate that there are statistical structures present in the data that cannot be captured by a GARCH model, or any of its variants. This result has important implications for the interpretation of the recent voluminous literature which attempts to model financial asset returns using this family of models.

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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.

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A number of tests for non-linear dependence in time series are presented and implemented on a set of 10 daily sterling exchange rates covering the entire post Bretton-Woods era until the present day. Irrefutable evidence of non-linearity is shown in many of the series, but most of this dependence can apparently be explained by reference to the GARCH family of models. It is suggested that the literature in this area has reached an impasse, with the presence of ARCH effects clearly demonstrated in a large number of papers, but with the tests for non-linearity which are currently available being unable to classify any additional non-linear structure.

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An alternative procedure to that of Lo is proposed for assessing whether there is significant evidence of persistence in time series. The technique estimates the Hurst exponent itself, and significance testing is based on an application of bootstrapping using surrogate data. The method is applied to a set of 10 daily pound exchange rates. A general lack of long-term memory is found to characterize all the series tested, in sympathy with the findings of a number of other recent papers which have used Lo's techniques.

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In this article, we apply the recently developed threshold autoregression model to examine both linearity and stationarity of Italy's real exchange rate vis--vis her six trading partner (G6) countries. Our main finding is that Italy's real exchange rate is a nonlinear process that is not characterized by a unit root process for five of six trading partner countries. This provides strong support for purchasing power parity.

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This paper reports results from a forecasting study for inflation, industrial output and exchange rates for India. We cannot reject the null hypothesis for linearity for all series used except for the growth rate of the foreign exchange series and our analysis is based on linear models, ARIMA and bivariate transfer functions and restricted VAR. Forecasting performance is evaluated using the models’ root mean-squared error differences and Theil’s inequality coefficients from recursive origin static, fixed origin dynamic and rolling origin dynamic forecasts. For models based on weekly data, based on RMSEs, we find that the bivariate models improve upon the forecasts of the ARIMA model while for models based on monthly data the ARIMA model has almost always better performance. In choosing between the two bivariate models on the basis of RMSEs, our overall results tend to support the use of a restricted VAR, as this model had the best forecasting performance more frequently than the transfer function model.

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Three alternative monetary models of exchange rate are tested using data on the Italian lira - US doIIar exchange rate. II is shown that up to the early 1990s these economic models perform better than the random walk model in out-of-sample forecasts.

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In this article, we consider the stability of the real effective exchange rates for four Pacific Island countries using the Lee and Strazicich (2003a, b) unit root test, which allows one to incorporate at most two structural breaks in the data series. Our main finding is that for Papua New Guinea and Samoa, exchange rates are stable, implying that shocks will have a transitory effect on real effective exchange rates, while for Fiji and the Solomon Islands we find exchange rates to be unstable, implying that shocks will have a permanent effect on real effective exchange rates.

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The paper examines the stationarity of India’s real exchange rate vis-a` -vis 16 of its major trading partner countries for the period 1960–2000. Application of the conventional ADF unit root test, the Lagrange multiplier (LM) unit root test with one structural break, and the LM unit root test with two structural breaks provides evidence that India’s exchange rate vis-a` -vis 15 out of 16 countries is stationary, implying support for purchasing power parity.

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The goal of this paper is to examine evidence for co-integration between nominal exchange rates for Canada, the UK, Japan, Germany, Italy and France (G6) vis-à-vis the US dollar, and the relative price ratios using monthly data over the period 1973:01 to 1997:04. Motivated by the fact that exchange rate adjustment may be asymmetric, we allowed for asymmetric adjustment in exchange rates by using the threshold autoregressive model and the momentum threshold autoregressive model. We do not find any evidence of a co-integrating relationship; hence, we fail to establish long-run purchasing power parity.

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In this paper, we apply several variants of the EGARCH model to examine the role of depreciation of the Indian rupee on India's stock market returns using daily data. Our findings suggest that volatility persistence has been high; depreciation of the rupee has increased volatility; and asymmetric volatility confirms that negative shocks generate more volatility than positive shocks. We also find that an appreciation of the Indian rupee over the 2002 to 2006 has generated more returns and less volatility.

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This article examines the long-run and short-run relationship between China's real exchange rate, foreign exchange reserves and the real interest rate differential between China and the United States using monthly data from 1980 to 2002. Extensive testing for unit roots allowing for up to two structural breaks in the trend indicates that the variables are not integrated of the same order. Thus, the bounds testing approach to cointegration is used, which finds that there is a single long-run relationship between the three variables. In the long run the real exchange rate has a statistically significant positive effect on foreign exchange reserves. The coefficient on the real interest rate differential is also positive, but is statistically insignificant. In the short-run it is found that the relationship between the real exchange rate, real interest rate differential and foreign exchange reserves is non-monotonic.