Journal articles: 'Exchange rates – Econometric models'

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Ford, J. L., Paul De Grauwe, and Theo Peeters. "Exchange Rates in Multicountry Econometric Models." Economic Journal 95, no. 378 (June 1985): 518. http://dx.doi.org/10.2307/2233243.

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Edwards, Sebastian. "Exchange rates in multi-country econometric models." Journal of International Economics 19, no. 3-4 (November 1985): 387–90. http://dx.doi.org/10.1016/0022-1996(85)90047-9.

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Berdinazarov, Zafar, Khasanjon Dodoev, Jamshid Mamasalaev, and Jakhongirmirzo Fakhodjonov. "Determinants of Exchange Rate Fluctuations of Uzbek Sum." Business and Management Studies 5, no. 1 (March 20, 2019): 52. http://dx.doi.org/10.11114/bms.v5i1.4162.

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This paper examines the determinants of exchange rate fluctuations of Uzbek sum by using three econometric models OLS (Ordinary Least Squares), ARIMA (Autoregressive Integrated Moving Average) and ML ARCH (Multivariate Long memory Autoregressive Conditional Heteroskadasticity). Model results show that the effects of money supply and remittances to the nominal and real exchange rates (USD/UZS) are found statistically significant; the impacts of inflation and interest rate are not econometrically meaningful. Also, it should be noted that the level of net trade influences to the exchange rate is not conclusive in our econometric analysis.

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Chen, An-Sing, and Mark T. Leung. "Dynamic Foreign Currency Trading Guided by Adaptive Forecasting." Review of Pacific Basin Financial Markets and Policies 01, no. 03 (September 1998): 383–418. http://dx.doi.org/10.1142/s0219091598000247.

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The difficulty in predicting exchange rates has been a long-standing problem in international finance as most standard econometric methods are unable to produce significantly better forecasts than the random walk model. Recent studies provide some evidence for the ability of multivariate time-series models to generate better forecasts. At the same time, artificial neural network models have been emerging as alternatives to predict exchange rates. In this paper we propose a nonlinear forecast model combining the neural network with the multivariate econometric framework. This hybrid model contains two forecasting stages. A time series approach based on Bayesian Vector Autoregression (BVAR) models is applied to the first stage of forecasting. The estimates from BVAR are then used by the nonparametric General Regression Neural Network (GRNN) to generate enhanced forecasts. To evaluate the economic impact of forecasts, we develop a set of currency trading rules guided by these models. The optimal conditions implied by the investment rules maximize the expected profits given the expected changes in exchange rates and the interest rate differentials between domestic and foreign countries. Both empirical and simulation experiments suggest that the proposed nonlinear adaptive forecasting model not only produces better forecasts but also results in higher investment returns than other types of models. The effect of risk aversion is also considered in the investment simulation.

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ZIMMERMANN, GEORG, RALPH NEUNEIER, and RALPH GROTHMANN. "MULTI-AGENT MARKET MODELING OF FOREIGN EXCHANGE RATES." Advances in Complex Systems 04, no. 01 (March 2001): 29–43. http://dx.doi.org/10.1142/s021952590100005x.

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A market mechanism is basically driven by a superposition of decisions of many agents optimizing their profit. The macroeconomic price dynamic is a consequence of the cumulated excess demand/supply created on this micro level. The behavior analysis of a small number of agents is well understood through the game theory. In case of a large number of agents one may use the limiting case that an individual agent does not have an influence on the market, which allows the aggregation of agents by statistic methods. In contrast to this restriction, we can omit the assumption of an atomic market structure, if we model the market through a multi-agent approach. The contribution of the mathematical theory of neural networks to the market price formation is mostly seen on the econometric side: neural networks allow the fitting of high dimensional nonlinear dynamic models. Furthermore, in our opinion, there is a close relationship between economics and the modeling ability of neural networks because a neuron can be interpreted as a simple model of decision making. With this in mind, a neural network models the interaction of many decisions and, hence, can be interpreted as the price formation mechanism of a market.

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Panopoulou, Ekaterini, and Theologos Pantelidis. "Regime-switching models for exchange rates." European Journal of Finance 21, no. 12 (April 9, 2014): 1023–69. http://dx.doi.org/10.1080/1351847x.2014.904240.

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Panda, Ajaya Kumar, Swagatika Nanda, Vipul Kumar Singh, and Satish Kumar. "Evidence of leverage effects and volatility spillover among exchange rates of selected emerging and growth leading economies." Journal of Financial Economic Policy 11, no. 2 (May 7, 2019): 174–92. http://dx.doi.org/10.1108/jfep-03-2018-0042.

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Purpose The purpose of this study is to examine the evidences of leverage effects on the conditional volatility of exchange rates because of asymmetric innovations and its spillover effects among the exchange rates of selected emerging and growth-leading economies. Design/methodology/approach The empirical analysis uses the sign bias test and asymmetric generalized autoregressive conditional heteroskedasticity (GARCH) models to capture the leverage effects on conditional volatility of exchange rates and also uses multivariate GARCH (MGARCH) model to address volatility spillovers among the studied exchange rates. Findings The study finds substantial impact of asymmetric innovations (news) on the conditional volatility of exchange rates, where Russian Ruble is showing significant leverage effect followed by Indian Rupee. The exchange rates depict significant mean spillover effects, where Rupee, Peso and Ruble are strongly connected; Real, Rupiah and Lira are moderately connected; and Yuan is the least connected exchange rate within the sample. The study also finds the assimilation of information in foreign exchanges and increased spillover effects in the post 2008 periods. Practical implications The results probably have the implications for international investment and asset management. Portfolio managers could use this research to optimize their international portfolio. Policymakers such as central banks may find the study useful to monitor and design interventions strategies in foreign exchange markets keeping an eye on the nature of movements among these exchange rates. Originality/value This is one of the few empirical research studies that aim to explore the leverage effects on exchange rates and their volatility spillovers among seven emerging and growth-leading economies using advanced econometric methodologies.

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Ahmed, KHATTAB, and SALMI Yahya. "Modeling Sources of Asymmetry in the Volatility of the Moroccan Dirham Exchange Rate." Applied Economics and Finance 8, no. 4 (July 26, 2021): 31. http://dx.doi.org/10.11114/aef.v8i4.5232.

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The main objective of this paper is to study the sources of asymmetry in the volatility of the bilateral exchange rates of the Moroccan dirham (MAD), against the EUR and the USD using the asymmetric econometric models of the ARCH-GARCH family. An empirical analysis was conducted on daily central bank data from March 2003 to March 2021, with a sample size of 4575 observations. Central bank intervention in the foreign exchange (interbank) market was found to affect the asymmetry in the volatility of the bilateral EUR/MAD and USD/MAD exchange rates. Specifically, sales of foreign exchange reserves by the monetary authority cause a fall in the exchange rate, which means that the market response to shocks is asymmetric. Finally, the selection criterion (AIC) allowed us to conclude that the asymmetric model AR(1)-TGARCH(1,1) is adequate for modeling the volatility of the exchange rate of the Moroccan dirham.

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Bozhechkova, A. V., S. G. Sinelnikov-Murylev, and P. V. Trunin. "Factors of the Russian ruble exchange rate dynamics in the 2000s and 2010s." Voprosy Ekonomiki, no. 8 (August 3, 2020): 5–22. http://dx.doi.org/10.32609/0042-8736-2020-8-5-22.

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The article discusses the key factors of the ruble exchange rate dynamics, analyzes the features of Russian currency market in the context of inflation targeting and the application of the budget rule. The basic theoretical approaches to modeling the dynamics of real and nominal exchange rates are presented, including behavioral models of the exchange rate, the monetary model of the exchange rate, and the hypothesis of uncovered interest parity. The most important factors of long-term and short-term dynamics of the exchange rate are revealed. The results of an econometric evaluation of the models of the real and nominal ruble exchange rates using dynamic least squares method (DOLS) are presented. It is shown that the key factors shaping the dynamics of the nominal ruble exchange rate are the terms of trade, the interest rate spread, the VIX volatility index, and the operations of the Russian Ministry of Finance under the budget rule. The long-term trajectory of the real exchange rate is formed by the terms of trade conditions, the Balassa—Samuelson effect, the dynamics of net foreign assets of the private sector.

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Anderson, Bing, Peter J. Hammond, and Cyrus A. Ramezani. "Affine Models of the Joint Dynamics of Exchange Rates and Interest Rates." Journal of Financial and Quantitative Analysis 45, no. 5 (August 13, 2010): 1341–65. http://dx.doi.org/10.1017/s0022109010000438.

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AbstractThis paper extends the affine class of term structure models to describe the joint dynamics of exchange rates and interest rates. In particular, the issue of how to reconcile the low volatility of interest rates with the high volatility of exchange rates is addressed. The incomplete market approach of introducing exchange rate volatility that is orthogonal to both interest rates and the pricing kernels is shown to be infeasible in the affine setting. Models in which excess exchange rate volatility is orthogonal to interest rates but not orthogonal to the pricing kernels are proposed and validated via Kalman filter estimation of maximal 5-factor models for 6 country pairs.

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Gupta, Sanjeev, and Sachin Kashyap. "Modelling volatility and forecasting of exchange rate of British pound sterling and Indian rupee." Journal of Modelling in Management 11, no. 2 (May 9, 2016): 389–404. http://dx.doi.org/10.1108/jm2-04-2014-0029.

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Purpose The paper aims to analyse the extent of volatility and generating forecasts of exchange rates of British pound and Indian rupees in US terms. Design/methodology/approach This study applies different combinations of GARCH and EGARCH models suggested in the Econometric literature to capture the extent of volatility. The forecast of exchange rates of British Pound and Indian Rupees in US terms are generated applying artificial neural network (ANN) technique using different combination of networks with hyperbolic tangent function at hidden and output stage of the model. Findings The presence of volatility depicts that there is noise and chaos in the forex market. Prediction of exchange rate of the respective currencies underscores that exchange rates will increase marginally in near future. Practical Implications The results proposed in this study will be benchmark for the hedgers, investors, bankers, practitioners and economists to foresee the exchange rate in the presence of volatility and design policies accordingly. Originality/value In literature, no study has applied ANN for forecasting exchange rate after measuring the extent of volatility. The present study is a unique contribution in the existing pool of literature to forecasts the concerned variable(s) after ascertaining the noise and chaos in the data by applying GARCH family models.

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Manikandan, Narayanan, and Srinivasan Subha. "Software Design Challenges in Time Series Prediction Systems Using Parallel Implementation of Artificial Neural Networks." Scientific World Journal 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/6709352.

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Software development life cycle has been characterized by destructive disconnects between activities like planning, analysis, design, and programming. Particularly software developed with prediction based results is always a big challenge for designers. Time series data forecasting like currency exchange, stock prices, and weather report are some of the areas where an extensive research is going on for the last three decades. In the initial days, the problems with financial analysis and prediction were solved by statistical models and methods. For the last two decades, a large number of Artificial Neural Networks based learning models have been proposed to solve the problems of financial data and get accurate results in prediction of the future trends and prices. This paper addressed some architectural design related issues for performance improvement through vectorising the strengths of multivariate econometric time series models and Artificial Neural Networks. It provides an adaptive approach for predicting exchange rates and it can be called hybrid methodology for predicting exchange rates. This framework is tested for finding the accuracy and performance of parallel algorithms used.

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Bissoondeeal, Rakesh K., Jane M. Binner, and Thomas Elger. "Monetary models of exchange rates and sweep programs." Applied Financial Economics 19, no. 14 (July 2009): 1117–29. http://dx.doi.org/10.1080/09603100802375501.

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Martínez-García, Enrique, and Jens Søndergaard. "INVESTMENT AND REAL EXCHANGE RATES IN STICKY PRICE MODELS." Macroeconomic Dynamics 17, no. 2 (May 25, 2012): 195–234. http://dx.doi.org/10.1017/s1365100511000095.

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This paper investigates how the inclusion of capital in the workhorse new open economy macro model affects its ability to generate volatile and persistent real exchange rates. We show that capital accumulation facilitates intertemporal consumption smoothing and significantly reduces the volatility of the real exchange rate. Nonetheless, monetary and investment-specific technology (IST) shocks still induce more real exchange rate volatility and less consumption comovement than productivity shocks (with or without capital). We find that endogenous persistence is particularly sensitive to the inertia of the monetary policy rule even with persistent exogenous shocks. However, irrespective of whether capital is present, productivity and IST shocks trigger highly persistent real exchange rates, whereas monetary shocks do not. Moreover, we point out that IST shocks tend to generate countercyclical real exchange rates—unlike productivity or monetary shocks—but have the counterfactual effect of also producing excessive investment volatility and countercyclical consumption.

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Bissoondeeal, Rakesh K., Jane M. Binner, Muddun Bhuruth, Alicia Gazely, and Veemadevi P. Mootanah. "Forecasting exchange rates with linear and nonlinear models." Global Business and Economics Review 10, no. 4 (2008): 414. http://dx.doi.org/10.1504/gber.2008.020593.

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Engel, Charles. "Exchange Rates, Interest Rates, and the Risk Premium." American Economic Review 106, no. 2 (February 1, 2016): 436–74. http://dx.doi.org/10.1257/aer.20121365.

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The uncovered interest parity puzzle concerns the empirical regularity that high interest rate countries tend to have high expected returns on short term deposits. A separate puzzle is that high real interest rate countries tend to have currencies that are stronger than can be accounted for by the path of expected real interest differentials under uncovered interest parity. These two findings have apparently contradictory implications for the relationship of the foreign-exchange risk premium and interest-rate differentials. We document these puzzles, and show that existing models appear unable to account for both. A model that might reconcile the findings is discussed. (JEL E43, F31, G15)

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RICHARDS, GORDON R. "FRACTALITY IN A MACROECONOMIC MODEL: NONLINEAR OSCILLATION AROUND A LONG-TERM EQUILIBRIUM." Fractals 10, no. 02 (June 2002): 235–51. http://dx.doi.org/10.1142/s0218348x02001063.

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Recent studies have established that macroeconomic time series exhibit fractal properties. Empirical tests here demonstrate that interest rates, exchange rates, output and prices all show evidence of a non-integer fractal dimension. Several classes of volatility models widely used in econometrics can give rise to fractality. In the paradigm proposed here, fractality results from multiplicative relationships between residual noise terms in simultaneous equation systems. The emergence of fractality in a large-scale econometric model is analyzed. The model uses well-established structural equations, so that all variables converge toward their equilibrium paths in the long run. The forecasted paths are then embedded in noise, and the model is re-simulated at a higher frequency. The simultaneity of the model equations causes the embedding noise to take on fractal properties. Multi-scaling demonstrates that the model simulations reproduce the fractal properties of the real-world time series reasonably well. Finally, it is possible to forecast at short horizons using an algorithm that exploits two aspects of fractality, scaling symmetries and intermittency. Ratios of rates of change capture proximate symmetries. A logit regression is used to predict the conditional probability of extreme events.

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Górecka, Anna, and Maciej Szmit. "Exchange rates prediction by ARIMA and neural networks models." International Advances in Economic Research 5, no. 4 (November 1999): 512. http://dx.doi.org/10.1007/bf02295548.

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Tarczyński, Waldemar, Sebastian Majewski, Małgorzata Tarczyńska-Łuniewska, Agnieszka Majewska, and Grzegorz Mentel. "The Impact of Weather Factors on Quotations of Energy Sector Companies on Warsaw Stock Exchange." Energies 14, no. 6 (March 10, 2021): 1536. http://dx.doi.org/10.3390/en14061536.

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Recent researches on behavioral finance have tested for, among others, evidence for the relations between weather, investors’ mood, and investment decisions. Many of the researches related to the influence of some weather factors, such as sunshine duration on stock exchange returns, but there is no complex research taking into account a wide group of weather factors determining investors’ mood. The main goal of the article is to verify the influence of weather factors on basic market parameters of energy sector companies quoted on the Warsaw Stock Exchange. Rates of return, trading volumes, and values of trading volume are taken into account during the research. All analyses are based on econometric models assuming the existence of typical problems of estimation such as: autocorrelation of residuals, heteroskedasticity, or abnormality of residuals. The best approximation of models was obtained for GARCH (Generalized Autoregressive Conditional Heteroskedasticity) type models.

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Kocabas, Ceren. "Testing for contagion in economic literature." Journal of Governance and Regulation 8, no. 3 (2019): 42–46. http://dx.doi.org/10.22495/jgr_v8_i3_p3.

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The contagion of the financial crisis is an unavoidable fact for the economies of the global system anymore. Therefore measuring contagion, analyzing the propagation of volatility across countries became mainly important research topics among economists. There are many different econometric techniques used to test for contagion effect of financial crises. Transmission of shocks from one country to another can be calculated with four different techniques. The empirical literature mostly based on the techniques of measuring cross-market correlations, GARCH models, cointegration and probit models. In these models, economists use financial or real indicators or both of them in their analyses. As the financial indicators, they generally use share price indices, interest rates, exchange rates, and inflation rate. As the real indicators, they generally use the values of GDP, imports, exports, unemployment rate, etc. The aim of this paper is to underline the prominent empirical studies in the field of contagious crises

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Hacioglu, Umit, Hasan Dincer, and Ismail Erkan Celik. "Conflict Risk and Its Implication on Economy and Financial System." International Journal of Finance & Banking Studies (2147-4486) 2, no. 2 (November 16, 2016): 109. http://dx.doi.org/10.20525/ijfbs.v2i2.638.

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<p>Considering the impacts of the conflict on the economic parameters in terms of macroeconomics, the following factors might affect the profitability of the company: foreign capital outflows, decrease in exports, increase in the interest rates, disruption of the investment climate, increase in the exchange rates, increase in the costs of import entry etc. Due to the expectable decrease in profit shares as to the investors, the contraction in the risk appetite will cause volatility in the prices of equity securities markets based on the impacts of the conflict, and the equity securities will depreciate. In this study, the main contributions on conflict risk and related econometric models have been discussed.</p>

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Castillo-Maldonado, Carlos Eduardo, and Fidel Pérez-Macal. "Assessment of Models to Forecast Exchange Rates: The Quetzal-U.S. Dollar Exchange Rate." Journal of Applied Economics 16, no. 1 (May 2013): 71–99. http://dx.doi.org/10.1016/s1514-0326(13)60004-5.

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KIANI, KHURSHID M. "FORECASTING FORWARD EXCHANGE RATE RISK PREMIUM IN SINGAPORE DOLLAR/US DOLLAR EXCHANGE RATE MARKET." Singapore Economic Review 54, no. 02 (June 2009): 283–98. http://dx.doi.org/10.1142/s0217590809003288.

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In this research, monthly forward exchange rates are evaluated for possible existence of time varying risk premia in Singapore forward foreign exchange rates against US dollar. The time varying risk premia in Singapore dollar is modeled using non-Gaussian signal plus noise models that encompass non-normality and time varying volatility. The results from signal plus noise models show statistically significant evidence of time varying risk premium in Singapore forward exchange rates although we failed to reject the hypotheses of no risk premium in the series. The results from Gaussian versions of these models are not much different and are in line with Wolff (1987) who also used the same methodology in Gaussian settings. Our results show statistically significant evidence of volatility clustering in Singapore forward exchange rates. The results from Gaussian signal plus noise models also show statistically significant evidence of volatility clustering and non-normality in Singapore forward foreign exchange rates. Additional tests on the series show that exclusion of conditional heteroskedasticity from the signal plus noise models leads to false statistical inferences.

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GNOATTO, ALESSANDRO. "COHERENT FOREIGN EXCHANGE MARKET MODELS." International Journal of Theoretical and Applied Finance 20, no. 01 (February 2017): 1750007. http://dx.doi.org/10.1142/s0219024917500078.

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A model describing the dynamics of a foreign exchange (FX) rate should preserve the same level of analytical tractability when the inverted FX process is considered. We show that affine stochastic volatility models satisfy such a requirement. Such a finding allows us to use affine stochastic volatility models as a building block for FX dynamics that are functionally-invariant with respect to the construction of suitable products/ratios of rates, thus generalizing the model of [A. De Col, A. Gnoatto & M. Grasselli (2013) Smiles all around: FX joint calibration in a multi-Heston model, Journal of Banking and Finance 37 (10), 3799–3818.].

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Sosa Castro, Magnolia Miriam, Christian Bucio Pacheco, and Héctor Eduardo Díaz Rodríguez. "Extreme volatility dependence in exchange rates." Cuadernos de Economía 40, no. 82 (February 4, 2021): 25–56. http://dx.doi.org/10.15446/cuadecon.v40n82.79400.

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This paper aims to analyse asymmetric volatility dependence in the exchange rate between the British Pound, Japanese Yen, Euro, and Mexican Peso compared to the U.S. dollar during different periods of turmoil and calm sub-periods between (1994-2018). GARCH and TARCH models are employed to model conditional

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Rötheli, Tobias. "Heuristics versus econometrics as a basis for forecasting international inflation differentials." foresight 21, no. 2 (April 8, 2019): 216–26. http://dx.doi.org/10.1108/fs-07-2018-0070.

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Purpose This study aims to address the issue of prediction of inflation differences for an economy that considers either fixing its exchange rate or joining a currency union. In this setting, individual countries have limited control over their inflation, and anticipating the possible course of domestic inflation relative to inflation abroad becomes an important input in policy-making. In this context, the author compares simple forecast heuristics and econometric modeling. Design/methodology/approach The study compares two basically different approaches. The first approach of forecasting consists of simple heuristics. Various heuristics are considered that differ with respect to the economic reasoning that goes into quantifying the forecast rules. The simplest such forecasting heuristic suggests that the average over all available observations of inflation differentials should be taken as a predictor for the future. Bringing more economic insight to bear suggests a further heuristic according to which historical inflation differentials should be adjusted for changes in the nominal exchange rate. A further variant of this approach suggests that a forecast should exclusively rely on data from earlier times under a pegged exchange rate. A fundamentally different approach to prediction builds on dynamic econometric models estimated by using all available historical data independent of the currency regime. Findings The author studies three small member countries of the Eurozone, i.e. Finland, Luxembourg and Portugal. For the evaluation of the various forecasting strategies, he performs out-of-sample predictions over a horizon of five years. The comparison of the four different forecasting strategies documents that the variant of the forecast heuristic that draws on data from earlier experiences under fixed exchange rates performs better than the forecast based on the estimated econometric model. Practical implications The findings of this study provide helpful guidelines for countries considering either joining a currency union or fixing their exchange rate. The author shows that a simple forecasting heuristic gives sound advice for assessing the likely course of inflation. Originality/value This study describes how economic theory can guide the selection of historical data for assessing likely future developments. The analysis shows that using a simple heuristic based on historical analogy can lead to better forecasts than the analytically more sophisticated approach of econometric modeling.

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DE LOS RIOS, ANTONIO DIEZ. "Can Affine Term Structure Models Help Us Predict Exchange Rates?" Journal of Money, Credit and Banking 41, no. 4 (June 2009): 755–66. http://dx.doi.org/10.1111/j.1538-4616.2009.00230.x.

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Sweeney, Richard J. "Mean Reversion in G-10 Nominal Exchange Rates." Journal of Financial and Quantitative Analysis 41, no. 3 (September 2006): 685–708. http://dx.doi.org/10.1017/s0022109000002581.

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AbstractAccording to conventional wisdom, industrial country floating exchange rates contain unit roots. SUR tests on panels of monthly Group of Ten (G-10) log nominal rates reject the null of unit roots for various samples over the current float with significance levels from 0.5% to 15%. On average, in out-of-sample forecasts mean reversion models beat random walks significantly in some forecast periods. For monthly data, the range of expected USD-DEM appreciation rates exceeds 15% per year in the mean reversion model. Mean reversion places strong restrictions on international models: over the sample period, the G-10 had to run monetary policies consistent with stable long-run nominal rates.

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Zhang, Guangfeng, Ian Marsh, and Ronald MacDonald. "A hybrid approach to exchange rates." Studies in Economics and Finance 33, no. 1 (March 7, 2016): 50–68. http://dx.doi.org/10.1108/sef-10-2014-0185.

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Purpose – This study aims to investigate the impact of information, both public macro news and private information, on exchange rate volatility in an integrated framework. Design/methodology/approach – The authors apply real-time data of macro announcements and high-frequency trading data (German Deutsche Mark to US dollar, DEM/USD, from 1 May to 31August 1996) to GARCH models and examine various model specifications. Findings – Data analysis demonstrates real-time macro news and market makers’ private information both have a significant impact on exchange rate volatility, but there is no interaction between macro and micro information in the information transmission process. Originality/value – This study contributes to empirical hybrid studies of examining exchange rates volatility, which is in line with literature that combine both macro and micro fundamentals in examining exchange rates variation. Particularly, a key element of this study is to use a microstructure fundamental variable, namely, order flow, to capture private information in an exchange rate volatility study.

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Li, Jinliang, Chihwa Kao, and Wei David Zhang. "Bounded influence estimator for GARCH models: evidence from foreign exchange rates." Applied Economics 42, no. 11 (April 2010): 1437–45. http://dx.doi.org/10.1080/00036840701721422.

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Chari, V. V., Patrick J. Kehoe, and Ellen R. McGrattan. "Can Sticky Price Models Generate Volatile and Persistent Real Exchange Rates?" Review of Economic Studies 69, no. 3 (July 2002): 533–63. http://dx.doi.org/10.1111/1467-937x.00216.

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Buncic, Daniel. "Understanding forecast failure of ESTAR models of real exchange rates." Empirical Economics 43, no. 1 (March 25, 2011): 399–426. http://dx.doi.org/10.1007/s00181-011-0460-5.

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Bunčák, Tomáš. "Exchange Rates Forecasting: Can Jump Models Combined with Macroeconomic Fundamentals Help?" Prague Economic Papers 25, no. 5 (January 1, 2016): 527–46. http://dx.doi.org/10.18267/j.pep.581.

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Love, Ryan, and Richard Payne. "Macroeconomic News, Order Flows, and Exchange Rates." Journal of Financial and Quantitative Analysis 43, no. 2 (June 2008): 467–88. http://dx.doi.org/10.1017/s0022109000003598.

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AbstractIn textbook models of exchange rate determination, the news contained in public information announcements is directly impounded into prices with there being no role for trading in this process of information assimilation. This paper directly tests this theoretical result using transaction level exchange rate return and trading data and a sample of scheduled macroeconomic announcements. The main result of the paper is that even information that is publicly and simultaneously released to all market participants is partially impounded into prices via the key micro level price determinant—order flow. We quantify the role that order flow plays and find that approximately one third of price-relevant information is incorporated via the trading process.

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Kodama, Osamu, LukĂˇĹˇ Pichl, and Taisei Kaizoji. "REGIME CHANGE AND TREND PREDICTION FOR BITCOIN TIME SERIES DATA." CBU International Conference Proceedings 5 (September 23, 2017): 384–88. http://dx.doi.org/10.12955/cbup.v5.954.

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Bitcoin time series dataset recording individual transactions denominated in Euro at the COINBASE market between April 23, 2015 and August 15, 2016 is analyzed. Markov switching model is applied to classify the regions of varying volatility represented by three hidden state regimes using univariate autoregressive model and dependent mixture model. Causality extraction and price prediction of daily BTCEUR exchange rates is performed by means of a recurrent neural network using the standard Elman model. Strong correlations is found between the normalized mean squared error of the Elman network (out-of-sample 5-day-ahead prediction) and the realized volatility (sum of minute returns squared throughout the trading day). The present approach is calibrated using simulated regime change in standard econometric models. Our results clearly demonstrate the applicability of recurrent neural networks to causality extraction even in the case of highly volatile cryptocurrency exchange rate time series data.

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ROSSI, BARBARA. "ARE EXCHANGE RATES REALLY RANDOM WALKS? SOME EVIDENCE ROBUST TO PARAMETER INSTABILITY." Macroeconomic Dynamics 10, no. 1 (December 14, 2005): 20–38. http://dx.doi.org/10.1017/s1365100506050085.

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Many authors have documented that it is challenging to explain exchange rate fluctuations with macroeconomic fundamentals: a random walk forecasts future exchange rates better than existing macroeconomic models. This paper applies newly developed tests for nested models that are robust to the presence of parameter instability. The empirical evidence shows that for some countries we can reject the hypothesis that exchange rates are random walks. This raises the possibility that economic models were previously rejected not because the fundamentals are completely unrelated to exchange rate fluctuations, but because the relationship is unstable over time and, thus, difficult to capture by Granger causality tests or by forecast comparisons. We also analyze forecasts that exploit the time variation in the parameters and find that, in some cases, they can improve over the random walk.

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Penezić, Nenad, Goran Anđelić, Marko Milošević, and Vilmoš Tot. "Application of modified GARCH methodology: Developed financial markets versus emerging financial markets." Serbian Journal of Management 15, no. 2 (2020): 241–61. http://dx.doi.org/10.5937/sjm15-20566.

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The subject of this research is to analyze and test the modified GARCH methodology in terms of quantifying the impact of inflation rates, interest rates on government bonds, reference interest rates, and exchange rates on daily rates of return on investment activities in the observed financial markets of North America, Serbia and Croatia. The aim of the research, i.e. a special focus in the research, is to compare the obtained results between the developed financial markets and the financial markets of developing countries, as well as to test the modified GARCH methodology in the observed financial markets. The key indicators in the research, presumed to affect the daily return rates, were the following: inflation rate, interest rates on government bonds, reference interest rate and exchange rate. The time period covered by the research is from 2005 to 2017, where the width of the research time horizon allows testing the modified GARCH methodology in the periods before, during and after the global financial crisis. In addition to the use of modified GARCH econometric models, the research methodology includes the use of AIC, SIC and HQC (Akaike, Schwarz and Hannan-Quinn) criteria for selecting the best models, as well as the appropriate tests that are suitable for and/or adapted to the specific characteristics of financial markets of both developed and developing countries. The research results confirm the role and importance of the modified GARCH methodology for effective investment risk quantification in developed financial markets versus the financial markets of developing countries. In this sense, the obtained research results will be useful to both the academic community and the professional public in the context of investment decision making.

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Zaród, Jadwiga. "Czynniki kształtujące ceny wybranych produktów rolno żywnościowych." Zeszyty Naukowe SGGW w Warszawie - Problemy Rolnictwa Światowego 17(32), no. 3 (September 30, 2017): 298–307. http://dx.doi.org/10.22630/prs.2017.17.3.75.

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Price differences significantly shape trade and affect consumer behavior. Change in prices of agricultural products imply changes in food prices. Factors shaping the prices of agri-food products can divide into structural factors (for example: area of crops, consumption, import, export) and cyclical factors (for example: extreme weather events, exchange rates). The purpose of this article is to study the influence of supply and demand factors on the purchase prices of selected products on the EU and Polish markets. The main research methods are the econometric causal-effect models. In addition, trend models will allow to determine the direction of development for the prices of analyzed agri-food products. OECD, FAO and EUROSTAT data were used to this study. The results show the relationship between the purchase price of agri-food products and supply and demand factors and allow comparison of these prices in Poland and in the EU. Trend models have helped to set price forecasts for the next two years.

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Phillips, Shauna, and Fredoun Z. Ahmadi-Esfahani. "Exchange rates and foreign direct investment: theoretical models and empirical evidence*." Australian Journal of Agricultural and Resource Economics 52, no. 4 (December 2008): 505–25. http://dx.doi.org/10.1111/j.1467-8489.2008.00431.x.

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Guisinger, Alexandra, and David Andrew Singer. "Exchange Rate Proclamations and Inflation-Fighting Credibility." International Organization 64, no. 2 (April 2010): 313–37. http://dx.doi.org/10.1017/s0020818310000056.

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AbstractIf governments choose economic policies that often run counter to their public commitments, are those commitments meaningless? We argue that government proclamations can be critical in signaling economic policy intentions. We focus on the realm of exchange rate policy, in which countries frequently implement an exchange rate regime that differs from the officially declared regime. We argue that the official exchange rate regime is one of the most important signals of a government's economic policy preferences. When a government makes a de jure public commitment to a fixed exchange rate, it sends a signal to domestic and international markets of its strict monetary-policy priorities. In contrast, a government that proclaims a floating exchange rate signals a desire to retain discretion over monetary policy, even if it has implemented a de facto fixed rate. We use data on 110 developed and developing countries from 1974 to 2004 to test two hypotheses: first, that governments that adopt de facto fixed exchange rates will experience less inflation when they back up their actions with official declarations; and second, that governments that abide by their commitments—as demonstrated by a history of following through on their public declarations of a fixed exchange rate regime—will establish greater inflation-fighting credibility. Within developing countries, democratic institutions enhance this credibility. Results from fixed-effects econometric models provide strong support for our hypotheses.

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Flood, R. P., and P. M. Garber. "The Linkage Between Speculative Attack and Target Zone Models of Exchange Rates." Quarterly Journal of Economics 106, no. 4 (November 1, 1991): 1367–72. http://dx.doi.org/10.2307/2937968.

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Kim, Byung-Yeon, and Iikka Korhonen. "Equilibrium exchange rates in transition countries: Evidence from dynamic heterogeneous panel models." Economic Systems 29, no. 2 (June 2005): 144–62. http://dx.doi.org/10.1016/j.ecosys.2005.03.005.

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Van der Geest, Willem. "Peter J. Montiel, Pierre-Richer Agenor, and Nadeem ul Haque. Informal Financial Markets in Developing Countries: A Macroeconomic Analysis. Published in the "Advances in Theoretical and Applied Economics" series edited by Homa Motamen-Scobie. Oxford: Blackwell. 1992. i-xi + 212 pp., including appendices. Hardbound. £40.00." Pakistan Development Review 32, no. 3 (September 1, 1993): 332–35. http://dx.doi.org/10.30541/v32i3pp.332-335.

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This volume reviews the nature and scope of informal financial markets in developing countries and elaborates on the theoretical and conceptual models which analyse 'financial repression' and other aspects of government intervention in financial markets. It also focuses on the consequences which the prevalence of informal financial markets in developing countries may have for monetary and exchange rate policy. In particular, it attempts to capture the functioning of informal, unregulated markets into macroeconomic models, working towards a general eqUilibrium model with informal financial markets. Two types of informal markets are analysed. The first are for informal lending at terms and conditions which differ greatly from those prevailing in the official banking system. The second are the 'parallel' markets for foreign exchange which tend to emerge in response to quantity restrictions on trade and administered allocation of foreign exchange to certain users at official rates, which are well below those on the parellel markets. The key question is whether these informal markets change the efficacy of monetary and credit policy-and, if they do, to what extent and in what direction? Two supporting appendices present econometric analyses of the efficiency of parallel currency markets and the degree of capital mobility in developing countries.

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Mishra, Prachi, and Antonio Spilimbergo. "Exchange Rates and Wages in an Integrated World." American Economic Journal: Macroeconomics 3, no. 4 (October 1, 2011): 53–84. http://dx.doi.org/10.1257/mac.3.4.53.

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We analyze how the pass-through from exchange rate to domestic wages depends on the degree of integration between domestic and foreign labor markets. Using data from 66 countries over the period 1981–2005, we find that the elasticity of domestic wages to real exchange rate is 0.15 after a year for countries with high barriers to external labor mobility, but about 0.40 in countries with low barriers to mobility. The result is robust to the inclusion of various controls, different measures of exchange rates, and definitions of labor market integration. These findings call for including labor mobility in macro models of external adjustment. (JEL F16, F31, J31)

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Zhu, Ke, Wai Keung Li, and Philip L. H. Yu. "Buffered Autoregressive Models With Conditional Heteroscedasticity: An Application to Exchange Rates." Journal of Business & Economic Statistics 35, no. 4 (April 25, 2017): 528–42. http://dx.doi.org/10.1080/07350015.2015.1123634.

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Devereux, Michael B., and Viktoria V. Hnatkovska. "Borders and Nominal Exchange Rates in Risk-Sharing." Journal of the European Economic Association 18, no. 3 (March 28, 2019): 1238–83. http://dx.doi.org/10.1093/jeea/jvz012.

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Abstract Models of risk-sharing predict that relative consumption growth rates are positively related to changes in real exchange rates. We investigate this hypothesis using a new multicountry and multiregional data set. Within countries, we find evidence for risk-sharing: episodes of high relative regional consumption growth are associated with regional real exchange rate depreciation. Across countries, however, the association is reversed: relative consumption and real exchange rates are negatively correlated. We define this reversal as a “border” effect. We find the border effect and show that it accounts for over half of the deviations from full risk-sharing. Since cross–border real exchange rates involve different currencies, it is natural to ask how much of the border effect is accounted for by movements in exchange rates. Our measures indicate that a large part of the border effect comes from nominal exchange rate fluctuations. We develop a simple open economy model that is consistent with the importance of nominal exchange rate variability in accounting for deviations from cross–country risk-sharing.

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Simon, György, and György Simon. "Some questions of world economic competition." Medjunarodni problemi 60, no. 2-3 (2008): 257–90. http://dx.doi.org/10.2298/medjp0803257s.

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The paper searches for an answer to the following questions: why had the situation in Japan and the European Union situation improved in comparison with the one in United States prior to the first oil price shock; what factors altered this tendency later, especially from the 1990s onwards; what was the role of the international economic conditions in all that? Applying the models of mathematical economics, the authors have proven their main statements by an econometric investigation. The most important conclusion that can be drawn is that in the world economic competition the situation both in Japan and the European Union was primarily determined by the changes in the world economic conditions, chiefly the oil prices in the world market and the exchange rates, what can less be said of the United States.

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Rossi, Barbara. "Exchange Rate Predictability." Journal of Economic Literature 51, no. 4 (December 1, 2013): 1063–119. http://dx.doi.org/10.1257/jel.51.4.1063.

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The main goal of this article is to provide an answer to the question: does anything forecast exchange rates, and if so, which variables? It is well known that exchange rate fluctuations are very difficult to predict using economic models, and that a random walk forecasts exchange rates better than any economic model (the Meese and Rogoff puzzle). However, the recent literature has identified a series of fundamentals/methodologies that claim to have resolved the puzzle. This article provides a critical review of the recent literature on exchange rate forecasting and illustrates the new methodologies and fundamentals that have been recently proposed in an up-to-date, thorough empirical analysis. Overall, our analysis of the literature and the data suggests that the answer to the question: “Are exchange rates predictable?” is, “It depends”—on the choice of predictor, forecast horizon, sample period, model, and forecast evaluation method. Predictability is most apparent when one or more of the following hold: the predictors are Taylor rule or net foreign assets, the model is linear, and a small number of parameters are estimated. The toughest benchmark is the random walk without drift. (JEL C53, F31, F37, E43, E52)

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Franses, Philip Hans, and Timo Teräsvirta. "INTRODUCTION TO THE SPECIAL ISSUE: NONLINEAR MODELING OF MULTIVARIATE MACROECONOMIC RELATIONS." Macroeconomic Dynamics 5, no. 4 (September 2001): 461–65. http://dx.doi.org/10.1017/s136510050102301x.

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During the past decade, the popularity of nonlinear models in econometrics has been increasing quite rapidly. Nonlinear models are now widely used for modeling macroeconomic relationships, and they also are used frequently in financial econometrics. The most popular nonlinear models have been univariate. Threshold autoregressive, Markov switching autoregressive, and smooth-transition autoregressive models, just to name a few popular families of models, have been widely applied to modeling of macroeconomic series. Even nonlinear multivariate single-equation models have found application in areas where linear single-equation models traditionally have been used, such as modeling the demand for money, real exchange rates, consumption–income relationship, and house prices. Interest in nonlinearities in the Phillips curve also has grown recently.

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Sultan, Julius Jhonny Sarungu, Albertus Maqnus Soesilo, and Siti Aisyah Tri Rahayu. "Oil price and Indonesian economic growth." Problems and Perspectives in Management 17, no. 1 (March 5, 2019): 152–62. http://dx.doi.org/10.21511/ppm.17(1).2019.14.

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Oil prices and economic growth are important indicators to see the success of Indonesia’s development performance. The use of oil as the world’s main energy source in general and Indonesia in particular is driven by industrialization. The more industries, the greater the energy resources needed. In the same context, economic growth will also increase oil demand. The purpose of this study is to examine and create empirical evidence of the relationship between world oil prices and economic growth towards domestic oil prices. Furthermore, to test and create empirical evidence on the relationship of domestic oil prices, agriculture, trade, investment, inflation, interest rates, industry, labor, exchange rates and balance of payments to economic growth. The expected output of this research will be to provide information on the policy of the transmission mechanism of oil prices and economic growth in Indonesia. The method used is descriptive and econometric approach to the analysis of simultaneous equation models with two stages of the least squares method. The results of the study indicate that there is a simultaneous relationship between oil prices and economic growth. Economic growth, world oil prices and domestic oil prices a year ago had a positive effect on domestic oil prices. The second result shows that domestic oil, agriculture, investment, interest rates, industry, exchange rates, balance of payments and economic growth in the previous year have a positive effect on economic growth, while trade, inflation and labor have a negative influence on economic growth.

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Journal articles on the topic 'Exchange rates – Econometric models'

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