Explaining Exchange Rate Research Articles

Explaining Exchange Rate Forecasts with Macroeconomic Fundamentals Using Interpretive Machine Learning

Explaining Exchange Rate Forecasts with Macroeconomic Fundamentals Using Interpretive Machine Learning

Can Time-Varying Currency Risk Hedging Explain Exchange Rates?

Can Time-Varying Currency Risk Hedging Explain Exchange Rates?

Does Economic Policy Uncertainty Explain Exchange Rate Movements in the Economic Community of West African States (ECOWAS): A Panel ARDL Approach

Research proposes that economic policy uncertainty (EPU) leads to exchange rate fluctuations. Given that African countries experience higher levels of uncertainty in developed/emerging markets, we examine the extent to which domestic and foreign EPU affect exchange rates for a panel of 12 ECOWAS countries covering the period 1996–2018. In order to account for non-stationarity, cross-sectional dependence, and heterogeneity, the paper employs the dynamic heterogeneous panel approach. The ECOWAS has a dual currency arrangement ranging from a common currency union (CFA) to floating exchange rates (Non-CFA). To account for this, this study splits the sample data into CFA and Non-CFA areas. In addition, this study considers the role of the global financial crisis in the exchange rate-EPU nexus. Our results show that domestic EPU has a positive effect on exchange rates in the long run for Non-CFA areas. Different from the existing literature, our results suggest that domestic EPU does not explain exchange rate fluctuations in the short run. For all countries, foreign EPU leads to appreciation in the long run and depreciation in the short run. Interestingly, foreign EPU has a more dominant effect on exchange rate fluctuations in the selected countries than domestic EPU. This may reflect the weak institutional framework in these countries, which allows external fluctuations to have a greater impact. Moreover, this could be attributed to the increase in foreign capital flows during the sample period. Thus, these countries must develop effective policies to effectively absorb these external shocks. Results are robust to different proxies of EPU.

Exchange rates and binary political events

Abstract This article introduces a rational expectations model that explains exchange rate dynamics and the predictability of forecast errors using private (aggregated via order flow) and public (probabilities of a binary event) information. We test the model for the periods leading up to the presidential impeachment vote in Brazil, the Brexit Referendum, and Donald Trump’s election in 2016. Proxies of the physical probabilities of these events reveal that they are a crucial source of pricing information for the BRL, GBP, and MXN currency pairs with the US dollar. They also explain forecast errors. The information content of order flow changes before and after an actual regime change resolves uncertainty.

EXCHANGE VALUE AS A MODERATED VARIABLES PROFITABILITY DETERMINANTS

The purpose of this study to determine the factors that affect the companys profitability. The independent variables include activity, capital structure and firm size. The moderating variable is the currency exchange rate. Design/methodology/approach: the subjects of this research are food and beverage sub-sector manufacturing companies listed on the Indonesia Stock Exchange from 2006-2017. The sampling method used purposive. Panel data were analyzed using multiple regression.. Finding: The result showed that the activity ratio had a positive effect, the solvency ratio had no effect, the size of the company had no effect on profitability. But the exchange rate can moderate the effect of solvency on profitability. Original/Value: This model was developed by including the exchange rate as a moderating variable. This is to explain exchange rate fluctuations, if there is currency depreciation, the amount of debt will increase which result in a decrease in profitability and vice versa. KEYWORDS: Firm Activity, Capital Structure, Firm Size, Exchange Rate and Profitability.

ТЕОРЕТИЧНІ ПІДХОДИ АНАЛІЗУ ВПЛИВУ ПАРИТЕТІВ НА ФОРМУВАННЯ ВАЛЮТНОГО КУРСУ ТА ВАЛЮТНОГО РИЗИКУ

Effective currency risk management is one of the most critical challenges for developing countries and emerging markets nowadays. Thus, it requires a comprehensive analysis of its causes, nature, factors, and possible consequences. Since the definition of a currency risk relates to unpredictable changes in exchange rates, its analysis means examining exchange rate volatility and formation. International parity conditions are one of the most straightforward and widespread approaches to explaining exchange rate formation. It includes purchasing power parity and interest parity. The first one is based on the law of one price and means the same purchasing power of currencies involved in buying a homogeneous product or a basket of goods in two countries under some conditions. Interest Rate Parity measures expected changes in nominal exchange rate by the difference in nominal interest rates at home and abroad. Nevertheless, clear theoretical foundations and empirical testing of theoretical assumptions have revealed contradictory results. It has led to several anomalies: Purchasing-Power-Parity Puzzle, Forward Premium Puzzle, and Forward Bias Puzzle. Despite all trials to solve the puzzles using new economic and econometric approaches to explain exchange rate volatility, there are constant and significant rebounds from theoretical models. Thus, we emphasize the need for a multidisciplinary approach to currency risk management that considers economic, political, and social factors. One possible method relates to improving existing models economically (adding new elements) or econometrically (applying the updated mathematical models). An alternative way is to analyze a currency risk as a systematic one depending on global factors. Consequently, the focus on exchange rate modeling and forecasting shifts to calculating and analyzing its premium. This approach might be the most prominent for the Ukrainian economy under postwar instability and fragility. Overall, this article provides valuable insights into the complex world of currency risks and offers practical recommendations for managing these risks in an uncertain global economy.

Liquidity and Exchange Rates: An Empirical Investigation

AbstractWe find strong empirical evidence that the liquidity yield on government bonds in combination with standard economic fundamentals can well account for nominal exchange rate movements. We find impressive evidence that changes in the liquidity yield are significant in explaining exchange rate changes for all the G10 countries, and we stress that the US dollar is not special in this relationship. We show how these relationships arise out of a canonical two-country New Keynesian model with liquidity returns. Additionally, we find a role for sovereign default risk and currency swap market frictions.

How did the oil price affect Japanese yen and other currencies? Fresh insights from the COVID-19 pandemic

In this paper, we use a shock spillover index to test the hypothesis that oil prices helped shape exchange rate behavior during the COVID-19 period. We use four exchange rates (CAD, EURO, JPY, and GBP vis-à-vis the USD) together with the oil price variable to test the importance of both return and volatility spillovers. Using hourly data, we consistently discover that both oil price return and volatility spillovers have become more important in explaining exchange rates in the COVID-19 period. • With hourly data, both oil price and volatility spillovers explain exchange rates in the COVID-19 period. • Oil prices explain exchange rates and exchange rates explain oil prices. • The effects are stronger over the COVID-19 period.

Role of Macroeconomic News Surprises in Explaining Exchange Rate Behavior

Role of Macroeconomic News Surprises in Explaining Exchange Rate Behavior

Can Time-Varying Currency Risk Hedging Explain Exchange Rates?

Can Time-Varying Currency Risk Hedging Explain Exchange Rates?

Can Time-Varying Currency Risk Hedging Explain Exchange Rates?

Can Time-Varying Currency Risk Hedging Explain Exchange Rates?

Measuring and explaining firm-level exchange rate exposure: The role of foreign market destinations and international trade

How does international trade affect the exchange rate exposure of firms? Trade induces greater economic exposure to exchange rate volatility. But more diversification in trade destinations and foreign supply and demand strategies may offer financial risk reduction depending on market conditions. In this paper, we focus on the role of trade and offer an integrated analysis on measuring and explaining exchange rate exposure. Using Dutch firm-level weekly data from 2011 to 2015, we find that: (1) distinguishable communities of firms based on their exchange rate exposure exist; (2) under varying market conditions, buying from and selling to foreign and more diverse markets is a way for firms to reduce exchange rate exposure; (3) firms that hedge during market downturns experience less exchange rate exposure. Our findings provide new insights for policy makers and investors interested in exchange rate exposure (measurement and drivers). • We use tail dependence networks for explaining exchange rate exposure. • Imports combined with exports lead to lower exchange rate risk. • Distinguishable groups of firms according to exchange rate exposure exist. • A greater number of geographic destinations reduces exchange rate exposure. • Firms that hedge can reduce exchange rate exposure only during market downturns.

Information content of order flows in the FX market: importance of nonfundamental factors

PurposeThe purpose of the paper is to show that order flows determine exchange rate dynamics because they carry information about nonfundamental factors besides macroeconomic fundamentals.Design/methodology/approachTo understand the role of nonfundamental factors in driving order flows, this study uses two approaches. Initially, Evans and Rime (2016) VAR framework is followed to study the incremental information transmitted by order flow compared to macroeconomic variables. Then, the study uses the settings in which Rime et al. (2010) conduct their empirical work, which gives the researcher more latitude in specifying the identity of the factors that drive order flows.FindingsThe findings evidence that order flows explain the dynamics of the TND/USD exchange rate. The results highlight that order flows convey information about technical strategies, the currency systematic factors and political risk. This study also documents the presence of a Ramadan effect in exchange rates and order flows.Originality/valueThis study makes four contributions to the literature. First, it complements the literature on the FX microstructure of emerging markets. The study investigates the information content carried by order flows, while the previous literature has focused solely on examining the explanatory power of order flows to explain exchange rates in emerging countries. The second contribution is that the study demonstrates formally that order flows determine exchange rates because they transmit information about nonfundamental factors. Third, this study is the first to examine whether order flows convey information about technical analysis. Four, the study relates order flow to nontraditional factors that are relevant to the Tunisian FX market.

Testing the Present‐Value Model of the Exchange Rate with Commodity Currencies

AbstractCountries that specialize in commodity exports often exhibit a correlation between the relevant commodity price and the value of their currency. We explore an explanation for this correlation based on the present‐value, monetary model of the exchange rate. An increase in the commodity price leads to an increase in the expected, future policy interest rate and so to an immediate appreciation. We test the model's over‐identifying restrictions for Canada, Australia, and New Zealand. There, controlling for the effect of commodity prices in predicting current and future monetary policy leaves those prices no significant, remaining role in statistically explaining exchange rates.

Dynamic pricing and exchange rate pass-through: Evidence from transaction-level data

Dynamic pricing is a widely employed pricing strategy for goods and services in which firms flexibly set prices, taking into account factors such as current market conditions. This paper studies the role this pricing strategy plays in explaining exchange rate pass-through in the context of package tour prices. We provide a theoretical model that illustrates how foreign producers and domestic retailers adjust prices to exchange rate fluctuations for three forms of dynamic pricing. Our model predicts that pass-through increases for clearance sales and with the capacity costs of producers in periods of high demand, while it decreases for advance purchases. We find robust empirical evidence for the model predictions using a unique German transaction-level data set of package tours at the daily frequency between 2012 and 2018 featuring rich variation in prices over time.

Can interest rate factors explain exchange rate fluctuations?

The level, slope, and curvature of the yield curve reflect time variation in investors’ risk premia and are known predictors of excess bond returns and economic activity. In this paper, I develop a term structure model under complete markets and no arbitrage to relate these interest rate factors to exchange rate fluctuations. The Gaussian properties of the stochastic discount factors imply non-linearities in exchange rate risk premia that are shown to account for up to half of the in-sample variation in one-year currency returns for different country pairs during the 1980s–2015 period. I find that interest rate factors help explain exchange rate fluctuations in and out of sample, particularly at longer horizons, and yield profitable currency portfolios relative to standard carry trade strategies.

Can Interest Rate Factors Explain Exchange Rate Fluctuations?

This paper explores whether interest rate factors, derived from the yield curve, can explain exchange rate fluctuations at different horizons. Using a dynamic term structure model under no-arbitrage, exchange rates are modeled as the ratio of two countries’ stochastic discount factors. Key to this framework is that factors are observable, which allows the model to be estimated by Maximum Likelihood. Results show that interest rate factors can explain half of the variation in one-year exchange rates and up to ninety percent of five-year movements, for free-floating currencies from 1999 to 2014. These findings suggest that yield curves contain important information for modeling exchange rate dynamics, particularly at longer horizons. JEL codes: G15, F31, E43 * Julieta Yung, Federal Reserve Bank of Dallas, Research Department, 2200 N. Pearl Street, Dallas, TX 75201. 214 922-5443. julieta.yung@dal.frb.org. I am grateful to Tom Cosimano, Jun Ma, Mark Wohar, and many others for helpful comments and suggestions. This paper also benefited from comments made by the participants at the Macroeconomics Seminar and the Mathematical Finance Research Group at the University of Notre Dame. The views in this paper are those of the author and do not necessarily reflect the views of the Federal Reserve Bank of Dallas or the Federal Reserve System.

Forward Premium Puzzle and Heterogeneous Beliefs

We propose a two-country model with heterogeneous beliefs to understand the forward premium puzzle. Facing a shock to the domestic money supply, the disagreement between domestic and foreign investors shifts the relative wealth of investors, which moves the exchange rate and interest rate differential in opposite directions. Calibrated to U.S. and U.K. data, our model reproduces the rejection of the uncovered interest rate parity. Using a monthly index of heterogeneous beliefs based on the Consensus Forecast in 15 major economies, the empirical evidence confirms that the dispersion of beliefs helps explain exchange rate movements and carry trade returns.

Exchange Rate Risk and Business Cycles

We show that currencies with a steeper yield curve tend to depreciate at business cycle horizons, in violation of uncovered interest parity. The yield curve adds no explanatory power over and above spot yield differentials in explaining exchange rates at longer horizons. Analysing bond holding period returns, we identify a tent-shaped relationship between the exchange rate risk premium and the relative slope across horizons. We derive this relationship analytically within an asset pricing framework and show it is driven by differences in transitory innovations to investors’ stochastic discount factor, captured by the relative yield curve slope and consistent with business cycle risk. Our mechanism is robust to the inclusion of liquidity yields, which instead contribute to explaining cross-sectional differences across currencies and reflect permanent innovations to investors’ stochastic discount factor.

Does non-linearity in exchange rate hold in Nigeria evidence from smooth transition autoregressive model

This study employs smooth transition autoregressive (STAR) model to investigate the non-linearity in exchange rate process in Nigeria within the context of exchange rate parity theory (ERPT). Quarterly data from 1981Q1 to 2017Q4 is used. The outcome of the study confirms the presence of exchange rate parity in Nigeria using Augmented Dickey Fuller (ADF) and Kwiatkowski-Phillips-Schmidt-Shin (KPSS) unit root tests. The study rejects the null hypothesis of linearity in nominal exchange rate in Nigeria. Furthermore, the estimation result of non-linear least squares (NLS) regression indicates that most of the parameter estimates are statistically significant. The study reveals that non-linear models best explain exchange rate dynamics in Nigeria. Likewise, the study discovers that exchange rate process in Nigeria is best fit with smoothly asymmetric logistic smooth transition autoregressive (LSTAR). The study concludes that heterogeneous nature of participants and asymmetric information in the market cause exchange rate to adjust in non-linear version.