Forecasting risk in the US Dollar exchange rate under volatility shifts

Recent evidence suggests that volatility shifts (i.e. structural breaks in volatility) in returns increases kurtosis which significantly contributes to the observed non-normality in market returns. In this paper, we endogenously detect significant shifts in the volatility of US Dollar exchange rate and incorporate this information to estimate Value-at-Risk (VaR) to forecast large declines in the US Dollar exchange rate. Our out-of-sample performance results indicate that a GARCH model with volatility shifts produces the most accurate VaR forecast relative to several benchmark methods. Our contribution is important as changes in US Dollar exchange rate have a substantial impact on the global economy and financial markets.     

Implied volatility term structure and exchange rate predictability

This paper provides empirical evidence of the predictive power of the currency implied volatility term structure (IVTS) for the behavior of the exchange rate from both cross-sectional and time series perspectives. Intriguingly, the direction of the prediction is not the same for developed and emerging markets. For developed markets, a high slope means low future returns, while for emerging markets it means high future returns. We analyze predictability from a cross-sectional perspective by building portfolios based on the slope of the term structure, and thus present a new currency trading strategy. For developed (emerging) currencies, we buy (sell) the two currencies with the lowest slopes and sell (buy) the two with the highest slopes. The proposed strategy performs better than common currency strategies – carry trade, risk reversal, and volatility risk premium (VRP) – based on the Sharpe ratio, considering only currency returns, which supports the exchange rate predictability of the IVTS from a cross-sectional perspective.     

Exchange rate misalignments,capital flows and volatility

This study investigates the effect of three dimensions of exchange rate misalignments—(i) distance (absolute misalignments), (ii) direction (overvaluation or undervaluation), and (iii) degree (small or large misalignments)—on the overall as well as short-cycle exchange rate volatility. Using data from 1988 to 2014, we find that relative PPP-based exchange rate misalignments increase exchange rate volatility. For developed and developing countries, this increase in volatility is driven mainly by large undervalued misalignments of the U.S. dollar. This finding might be linked to interventions targeting the loss in domestic producers’ competitiveness in global markets. Interestingly, in the case of developed countries, we find this adverse effect on exchange rate volatility also for small absolute misalignments; exchange rate movements close to equilibrium may be associated with ambiguity with respect to future movements in developed countries, which can result in higher exchange rate volatility. Further, the results suggest that, when the dollar is highly undervalued, capital flows have a stabilizing effect on exchange rate volatility in developed countries but a destabilizing effect in developing countries. The finding is consistent with investors’ strategy of taking exchange rate overvaluation and undervaluation into account when engaging in cross-border investments.     

The effect of nominal exchange rate volatility on real macroeconomic performance in the CEE countries

This paper analyzes the relation between nominal exchange rate volatility and several macroeconomic variables, namely real output growth, excess credit, foreign direct investment (FDI) and the current account balance, in the Central and Eastern European EU member states. Using panel estimations for the period between 1995 and 2008, we find that lower exchange rate volatility is associated with higher growth, higher stocks of FDI, higher current account deficits, and higher excess credit. At the same time, the recent evidence seems to suggest that following the global financial crisis, “hard peg” countries may have experienced a more severe adjustment process than “floaters”. The results are economically and statistically significant and robust.     

人民币汇率波动对NFDI波动的影响及其检验

本文通过对我国NFDI资本流动性及其波动性的计算,检验了人民币/美元汇率波动对NFDI波动性的关系。通过实证分析表明,人民币汇率的波动将导致NFDI资本流动的明显不稳定。在理论研究的基础上,引申出其政策含义：在国际资本流动不断加大的今天,我们必须维护人民币/美元汇率的稳定,这样对于有效引导NFDI的资本流动和维护金融稳定都具有重要的意义。     

Exchange rate volatility and Spanish-American commodity trade flows

A number of recent studies have tested the impact of exchange rate volatility on trade flows, particularly for individual commodities, for various country pairs. These have found that risk can increase as well as decrease trade, but that oftentimes industries are not affected. This study examines trade between the United States and Spain over the period from 1962 to 2009, for 131 U.S. export industries and 88 import industries. We find that exchange rate volatility has short-run and long-run effects in only a fraction of the cases, but that exports respond more to increased uncertainty than imports do. In all, only 35 of the 74 U.S. export industries are affected (11 positive, 24 negative), whilst only three out of 37 import industries have positive coefficients and 11 have negative ones. We find no evidence that durable or nondurable goods are more likely to respond to volatility, whilst small industries or specialized goods might show more of a positive response.     

The effect of exchange rate volatility on U.S. bilateral trade with Africa: A symmetric and asymmetric analysis

The impact of exchange rate volatility on U.S. trade with the world or on U.S. trade with major partners has been assessed by many researchers, but none have considered the case of U.S. trade with African nations. We fill this gap by assessing the symmetric and asymmetric impact of the real bilateral exchange rate volatility between the U.S. dollar and each African partner’s currency on the U.S. trade flows with each of the 20 partners from Africa. We found asymmetric short-run effects of exchange rate volatility on almost all U.S. exports to and imports from each of the 20 countries. In addition, significant long-run asymmetric effects were discovered in the case of U.S. exports to 15 countries and U.S. imports from 12 countries. Our findings are partner-specific.     

A new approach to capital control for emerging market economies

The present paper proposes a new approach to capital control for emerging market economies, which restricts capital inflows to a fraction of the gap between foreign currency denominated loans and deposits in the economy. We show that the foreign-currency-gap capital control proposed here outperforms tax-based capital control in attenuating the negative effects of external shocks on business cycle fluctuations. This attenuation effect works via the interest rate channel and the capital control constraint itself. Compared to tax-based capital control, the foreign-currency-gap capital control is welfare enhancing, effectively mitigating financial instability with little cost in terms of macroeconomic stability. Countries with a high level of foreign currency denominated loans and deposits need to implement a stricter foreign-currency-gap capital control.     

Time-varying risk aversion and renminbi exchange rate volatility: Evidence from CARR-MIDAS model

In this paper, we investigate the relation between time-varying risk aversion and renminbi exchange rate volatility using the conditional autoregressive range-mixed-data sampling (CARR-MIDAS) model. The CARR-MIDAS model is a range-based volatility model, which exploits intraday information regarding the intraday trajectory of the price. Moreover, the model features a MIDAS structure allowing for time-varying risk aversion to drive the long-run volatility dynamics. Our empirical results show that time-varying risk aversion has a significantly negative effect on the long-run volatility of renminbi exchange rate. Moreover, we observe that both intraday ranges and time-varying risk aversion contain important information for forecasting renminbi exchange rate volatility. The range-based CARR-MIDAS model incorporating time-varying risk aversion provides more accurate out-of-sample forecasts of renminbi exchange rate volatility compared to a variety of competing models, including the return-based GARCH, GARCH-MIDAS and GARCH-MIDAS incorporating time-varying risk aversion as well as range-based CARR, CARR-MIDAS and heterogeneous autoregressive (HAR), for forecast horizons of 1 day up to 3 months. This result is robust to alternative risk aversion measure, alternative MIDAS lags as well as alternative out-of-sample periods. Overall, our findings highlight the value of incorporating intraday information and time-varying risk aversion for forecasting the renminbi exchange rate volatility.     

The nexus between country risk and exchange rate regimes: A global investigation

Using a sample of 110 countries over the period 1984–2013, this paper examines the impacts of country risks on choosing a specific exchange rate regime (first by utilizing the Levy-Yeyati and Sturzenegger de facto classification and then robusting it by the IMF de jure measurement) relative to other regimes via the panel multinomial logit approach. Empirical findings are as follows. First, in the full samples case we provide evidence that government is more likely to implement a flexible regime, but less likely to adopt a fixed regime, under a low level of composite and financial risk. Second, we find that Eurozone countries are more likely to choose a fixed exchange rate regime with a decrease in the level of country risk and favor a flexible regime in response to a shock from an increase of risk, which is opposite to non-Eurozone countries. Third, we note that high-risk countries are more likely to choose a fixed regime with a low level of composite and political risk in the government, but do not adjust the exchange rate regime as a shock absorber when facing economic and financial risks. It is interesting to see that those countries with relatively low risk display almost opposite results versus high-risk economies. Overall, we believe that it is critically important to account for political economy variables in a government’s exchange rate policy decisions, especially for country risks. All results are robust to the panel ordered probit model.     

Incorporating the RMB internationalization effect into its exchange rate volatility forecasting

Recently, the Chinese government has launched the renminbi (RMB) internationalization policy as an impetus to foster China’s global economic integration. The RMB internationalization effect on China’s economy and the RMB exchange rate has attracted massive attention in recent financial research. In this paper, we adopt a genetic programming (GP) method to generate new RMB exchange rate volatility forecasting models incorporating the RMB internationalization effect. Our models are proved to have significant accuracy improvement in predicting both RMB/US dollar and RMB/euro exchange rate volatilities, compared with standard GARCH volatility models, which are incapable of capturing the RMB internationalization effect. Furthermore, our models display salient practical implications for policy makers to formulate monetary policies and currency traders to design effective trading strategies.     

Impact of an unexplained component of real exchange rate volatility on FDI: Evidence from transition countries

The aim of this paper is to examine the impact of an unexplained component of real exchange rate volatility on FDI in transition economies. We make an attempt to overcome some problems associated with previous studies; the aggregation problem, inadequate measures of volatility, short-run focus and the endogeneity problem. Using a GARCH specification, we focus on long-run volatility, while we control for the endogeneity problem by applying SYS-GMM estimation. The obtained results show that the impact of the unexplained component of real exchange rate volatility on FDI differs among economic activities since 2000. As part of the re-estimation exercise, we use two alternative measures of volatility to avoid arbitrariness. The obtained results are to a large extent in accordance with the first one.     

Testing the forward volatility unbiasedness hypothesis in exchange rates under long-range dependence

This paper analyses the unbiasedness hypothesis between spot and forward volatility, using both the actual and the continuous path of realised volatility, and focusing on long-memory properties. For this purpose, we use daily realised volatility with jumps for the USD/EUR exchange rate negotiated in the FX market and employ fractional integration and cointegration techniques. Both series have long-range dependence, and so does the error correction term of their long-run relationship. Hence, deviations from equilibrium are highly persistent, and the effects of shocks affecting the long-run relationship dissipate very slowly. While for long-term contracts, there is some empirical evidence that the forward volatility unbiasedness hypothesis does not hold – and, thus, that forward implied volatility is a systematically downward-biased predictor of future spot volatility – for short-term contracts, the evidence is mixed.     

Statistical learning and exchange rate forecasting

This study uses innovative tools recently proposed in the statistical learning literature to assess the capability of standard exchange rate models to predict the exchange rate in the short and long runs. Our results show that statistical learning methods deliver remarkably good performance, outperforming the random walk in forecasting the exchange rate at different forecasting horizons, with the exception of the very short term (a period of one to two months). These results were robust across countries, time, and models. We then used these tools to compare the predictive capabilities of different exchange rate models and model specifications, and found that sticky price versions of the monetary model with an error correction specification delivered the best performance. We also explain the operation of the statistical learning models by developing measures of variable importance and analyzing the kind of relationship that links each variable with the outcome. This gives us a better understanding of the relationship between the exchange rate and economic fundamentals, which appears complex and characterized by strong non-linearities.     

Exchange rate volatility and fluctuations in the extensive margin of trade

The existing evidence for exporters׳ entry and exit in response to exchange rate movements is based on either low frequency data or a sample with large devaluations. Using quarterly data of U.S. bilateral trade with 99 countries, this study provides new evidence that the extensive margin of trade fluctuates over the business cycle. First, I show that the extensive margin of exports to the U.S. and the extensive margin of imports from the U.S. are more volatile than the output of almost all trading partners. Next, I find that fixing exchange rates with the U.S. dollar, having a free trade agreement with the U.S., and an increase in country size is significantly associated with the stability of the pattern of trade with the U.S.     

Implied volatility and the risk-free rate of return in options markets

We numerically solve systems of Black–Scholes formulas for implied volatility and implied risk-free rate of return. After using a seemingly unrelated regressions (SUR) model to obtain point estimates for implied volatility and implied risk-free rate, the options are re-priced using these parameters. After repricing, the difference between the market price and model price is increasing in time to expiration, while the effect of moneyness and the bid-ask spread are ambiguous. Our varying risk-free rate model yields Black–Scholes prices closer to market prices than the fixed risk-free rate model. In addition, our model is better for predicting future evolutions in model-free implied volatility as measured by the VIX.     

Causality and volatility patterns between gold prices and exchange rates

This paper provides a new perspective on the link between gold prices and exchange rates. Based on gold prices denominated in five different currencies and the related bilateral exchange rates, we put causalities and short-run volatility transmission under closer scrutiny. We provide evidence that the identification of a strong hedge function of gold requires an explicit modeling of the volatility component. For all currencies, exchange rate depreciations initially have a negative impact on the gold price after one day which turns out to be positive after two days in most of the cases. Contrary to previous studies, our results point to a specific role of the dollar in the context of gold-exchange rate relationships: volatility of dollar exchange rates more frequently results in strong hedging functions of gold prices. Furthermore, the gold price denominated in the US dollar tends to increase after a depreciation of the dollar.     

An objective function for simulation based inference on exchange rate data

The assessment of models of financial market behaviour requires evaluation tools. When complexity hinders a direct estimation approach, e.g., for agent based microsimulation models, simulation based estimators might provide an alternative. In order to apply such techniques, an objective function is required, which should be based on robust statistics of the time series under consideration. Based on the identification of robust statistics of foreign exchange rate time series in previous research, an objective function is derived. This function takes into account stylized facts about the unconditional distribution of exchange rate returns and properties of the conditional distribution, in particular, autoregressive conditional heteroscedasticity and long memory. A bootstrap procedure is used to obtain an estimate of the variance-covariance matrix of the different moments included in the objective function, which is used as a base for the weighting matrix. Finally, the properties of the objective function are analyzed for two different agent based models of the foreign exchange market, a simple GARCH-model and a stochastic volatility model using the DM/US-$ exchange rate as a benchmark. It is also discussed how the results might be used for inference purposes. Research has been supported by the DFG grant WI 20024/2-1/2. We are indebted to two anonymous referees of this journal, Leigh Tesfatsion, Patrick Burns and other participants of the CEF’06 conference in Limassol for helpful comments on preliminary versions of this paper.     

Restricting capital outflow

According to the “Capital Asset Pricing Model”, an individual can increase his utility by diversifying his capital across countries. If that is the case, then why do governments impose restrictions on capital outflow? This paper argues that foreign owners of capital have less political power than domestic ones and therefore capital liberalization weakens the political power that protects capital, increases the taxation of capital and thus reduces total investment. Indeed, most of the empirical evidence suggests that capital liberalization is positively correlated with government expenditure, social security spending and corporate taxation.     

Balance sheets, exchange rate policy, and welfare

We evaluate the welfare implications of fixed and flexible exchange rate regimes in a small open-economy model that incorporates the financial accelerator coupled with liability dollarization. We solve the model up to a second-order approximation which allows us to rigorously address the relationship between uncertainty and welfare. We identify leverage and debt-to-GDP ratios above which an exchange rate peg is welfare superior to a flexible exchange rate regime. The results indicate that emerging market countries with even moderate levels of foreign currency-denominated debt may find it beneficial to stabilize their exchange rates.