Further on nonlinearity,persistence, and integration properties of real exchange rates

Integration, nonlinearity, and persistence dynamics of several quarterly US-Dollar-denominated real exchange rates are investigated by using new unit root tests, simulated p-values for linearity tests, estimation of smooth transition autoregressive (STAR) models, and simulation of autocorrelation functions. This paper uses a simulation-based approach to study covariance stationarity and persistence dynamics of the estimated models. Findings in the paper provide evidence of nonlinear mean reversion for several series albeit with some persistence. Results also reveal considerable variation in the degree of persistence and timing of switches across extreme regimes in ESTAR models between Euro and non-Euro area currencies.     

Random walk and efficiency tests in the Asia-Pacific foreign exchange markets: Evidence from the post-Asian currency crisis data

This paper empirically tests the random walk and efficiency hypothesis for 12 Asia-Pacific foreign exchange markets. The hypothesis is tested using individual as well as panel unit root tests and two variance-ratio tests. The study covers the high (daily) and medium (weekly) frequency post-Asian crisis spot exchange rate data from January 1998 to July 2007. The inferential outcomes do not differ substantially between the unit root tests and the variance-ratio tests when using daily data but differ significantly when using weekly data. With the daily data, both types of unit root tests identify unit root components for all the series and two variance-ratio tests provide the evidence of martingale behavior for majority of the exchange rates tested. With the weekly data, panel unit root tests identify unit root component for the exchange rates and, the unit root tests on a single series basis identify unit root component for 10 foreign exchange markets. However, the variance-ratio tests reject the martingale null for the majority of the exchange rates when using weekly data.     

Threshold cointegration,nonlinearity, and frequency domain causality relationship between stock price and Turkish Lira

Modelling complex asymmetric effects and non-linear relationships between exchange rate and stock prices has challenged classical econometric methods. This study contributes to the relative literature in the following distinct ways. First, we follow a variety of econometric approaches in order to characterize the complex dynamic co-movements between Turkish stock market and exchange rate from January 2003 to December 2018. Secondly, we show that the evidence for asymmetric threshold cointegration in Turkey’s financial market can be hidden by following linear time series methodologies. Thirdly, it is also worth noting that the real effective exchange rate, USD-Turkish lira exchange rates, money supply and interest rates have large predictive power for stock price fluctuations at various frequencies. Building on these insights, we claim that asymmetry (nonlinearity) is particularly important in Turkey’s financial market because it shows the need for a new pattern of policy measures to prevent financial market crisis risk in Turkey.     

Is the evidence for PPP reliable? A sustainability examination of the stationarity of real exchange rates

Some recent time series studies testing the stationarity of real exchange rates (RERs) produce conflicting results. Using nonlinear unit root tests and recursive analysis, this paper tests whether the evidence on the stationarity of RERs is sensitive to different numeraire currencies, different sample periods covering regional and global crises, and the inclusion of countries with different levels of economic or regional integration. The results indicate that evidence for a stationary RER could be substantially sensitive to sample period changes, but not so for the currencies of the countries involved in forming the euro area. We also find that financial crises have a notable impact on testing the stationarity of RERs, depending on the numeraire currency used. We discuss the policy implications of the findings.     

Los procesos α-estables y su relación con el exponente de autosimilitud: paridades de los tipos de cambio dólar estadounidense,dólar canadiense,euro y yen

In this research we analyze the performance of the exchange rates of USA Dollar, Canadian Dollar, Euro and Yen; we estimate the basic statistics, α-stable parameters, we performed tests of goodness fit Kolmogorov-Smirnov, Anderson-Darling and Lilliefors; we estimate self-similarity exponents and we performed t y F tests, ruling that the series of the exchange rates are multi-fractal; we estimate confidence intervals of the exchange rates and we conclude that the estimated α-stable distributions are more efficient than the gaussian distribution to quantify market risks and the series are self-similar; by the ? index we infer the risk of events and we indicate that exchange rates are anti-persistent, have mean reversión, short-term memory, negative correlation and high risk in the short and medium term; the estimation and validation of α-stable distributions and the exponent of self-similarity are important for pricing and the creation of innovative investment instruments by financial engineering, risk management and derivatives pricing.     

Nonlinear serial dependence and the weak-form efficiency of Asian emerging stock markets

The objective of this paper is to re-examine the weak-form efficiency of 10 Asian emerging stock markets. Using a battery of nonlinearity tests, the statistical results reveal that all the returns series still contain predictable nonlinearities even after removing linear serial correlation from the data. The next stage of sub-sample analysis using the Hinich [Hinich, M., 1996. Testing for dependence in the input to a linear time series model. Journal of Nonparametric Statistics 6, 205–221] bicorrelation test shows that the 10 Asian series follow a pure noise process for long periods of time, only to be interspersed with brief periods of strong nonlinear dependence. The exploratory investigation found that the cross-country differences in nonlinear departure from market efficiency can be explained by market size and trading activity, while the transient burst of nonlinear periods in each individual market can be attributed largely to the occurrence of economic and political events.     

The fractal structure of exchange rates: measurement and forecasting

Recent research has demonstrated that exchange rates have fractal properties. The mathematical definition of fractality is non-integer dimensionality. Statistically, this corresponds to intermittency, or inhomogeneity in a time series. Fractality in financial markets originates in systems with large numbers of equations. It is therefore stochastic fractality, which is separate and distinct from deterministic chaos. Other nonlinear models that have been used to forecast exchange rates, such as the ARCH group, do not exhibit fractality. At the same time, there are crucial differences between the fractal processes observed in financial markets and the multifractals identified in physics. In physics, fractals show strong scaling symmetries. In financial markets, this is not the case. Scaling symmetries are weak, and in the long run, exchange rates evolve toward a non-fractal state. Fractality in exchange rates is consistent with structural econometric models: differentials in rates of return across national boundaries generate both nonlinear variability and intermittency. Empirical tests demonstrate that out of 21 daily exchange rates, all scale as fractals. Short-term interest rates and interest rate differentials also show evidence of fractality. A forecasting algorithm based on state transitions is proposed.     

Searching for evidence of long-run PPP from a post-Bretton Woods panel: separating the wheat from the chaff

This paper reexamines the issue of long-run PPP using multiple panel tests in the framework of confirmatory analysis. Application of six panel tests under competing null hypotheses to the real exchange rates of 21 industrial countries yields seemingly contradictory evidence on the parity during the post-Bretton Woods period. Regardless of numeraire currency, four I(1) panel tests unanimously reject the null hypothesis in favor of long-run PPP, whereas two I(0) panel tests lend little support to the parity at conventional significance levels. Confirmatory analysis suggests that this puzzling result can be explained either by nonlinear dynamics of the real exchange rates or by a mixture of I(0) and I(1) series in the panel. Monte Carlo experiments indicate that potential mix of I(0) and I(1) series is more relevant to the empirical finding. The use of a sequential classification method sorts out six real exchange rates which exhibit most persistent deviations from long-run equilibrium. Systematic behavior of these series can be characterized better by country specific factors than by observable macroeconomic variables.     

Getting PPP right: Identifying mean-reverting real exchange rates in panels

Recent advances in testing for the validity of Purchasing Power Parity (PPP) focus on the time series properties of real exchange rates in panel frameworks. One weakness of such tests, however, is that they fail to inform the researcher as to which cross-section units are stationary. As a consequence, a reservation for PPP analyses based on such tests is that a small number of real exchange rates in a given panel may drive the results. In this paper we examine the PPP hypothesis focusing on the stationarity of the real exchange rates in up to 25 OECD countries. We introduce a methodology that when applied to a set of established panel unit-root tests, allows the identification of the real exchange rates that are stationary. Our results reveal evidence of mean-reversion that is significantly stronger as compared to that obtained by the existing literature, strengthening the case for PPP.     

The random-walk behavior of the Euro exchange rate

We use Generalized Andrews–Ploberger (GAP) tests to examine the random-walk behavior of 17 OECD countries’ euro exchange rates at daily frequencies. The GAP tests reject the hypothesis of random-walk behavior less often than do traditional tests. Moreover, the random-walk hypothesis cannot be rejected for the euro’s exchange rate against most of the major currencies. We also use the generalized Box–Pierce tests to produce evidence that corroborates the above findings. Finally, and in contrast to the traditional tests, the GAP tests produce results that are consistent during the great moderation and the recent global financial crisis periods.     

A Time Series Analysis of U.K. Construction and Real Estate Indices

This study assess the nonlinear behavior of U.K. Construction and Real Estate indices. Standard unit root tests show that both time series are I(1) processes. However, the empirical results show that the returns series for both indices deviate from the null hypothesis of white noise. Moreover, we have found evidence of nonlinearity but strong evidence against chaos for the returns series. Further tests show that the source of nonlinearity is rather different. Hence, the Construction index returns series displays weak nonlinear forecastability, typical of nonlinear deterministic processes, whereas the Real Estate index could be characterized as a stationary process about a nonlinear deterministic trend.     

The Intertemporal Relationship Between the Currency Spot Market and the Currency Option Market

This study examines the lead/lag relationship between currency option and currency spot markets for the Deutsche mark and the Japanese yen. Using intraday currency option transactions data for the year 1989 and applying a European type currency option pricing model, pair data series of the implied and the observed exchange rates are compiled. Causality tests are then employed to test the causal relation between the observed and the implied exchange rate changes. The results indicate that the currency spot market leads the currency option market by about ninety minutes.     

The confusing time-series behaviour of real exchange rates: Are asymmetries important?

Evidence regarding the time-series properties of real exchange rates is mixed. There is evidence that such rates exhibit both non-stationary and stationary behaviour. The current dominant belief is that rates are non-linear stationary, however, this is not accepted without question. This paper re-examines the time-series properties of five US dollar real exchange rates and argues that the confusing time-series properties arise largely as each series examined exhibits periods of non-stationary and stationary behaviour such that the sample over which any empirical exercise is conducted is of importance. However, extending a typical non-linear model used within the literature to allow for asymmetries improves the models ability to fit the data. Therefore, our results suggest that modelling asymmetries between positive and negative real exchange rate deviations is of importance, whereas extant research has typically rules out asymmetry. Indeed a forecasting exercise conducted over a 1-year horizon is particularly supportive of this model. Such a finding is of importance not only for academics but also finance practitioners involved in trading and portfolio management and finance managers who act in the foreign exchange market for goods market trading. It remains for future research to theoretically motivate the asymmetries found here.     

Oil price and FX-rates dependency

Oil prices and exchange rates against the dollar have both experienced long swings over the recent decade. Regardless of the great amount of research, some issues are still open to debate. In this vein, this paper focuses on the evolution of the relationship between oil prices and dollar exchange rates of 12 oil exporting and oil importing countries based on a dynamic copula approach. We use daily data for two 5-year periods between 2003 and 2013, taking the collapse of Lehman Brothers as the dividing point. Our results have four main implications: first, the intensity of relationship between oil prices and FX-rates has increased over time even if the peak of the financial crisis is included. Second, the increased tail dependency shows that extreme events are likelier to occur simultaneously for both series. Third, the dependency has become more dynamic after the financial crisis and is therefore better characterized by time-varying copulas. Finally, currencies of oil importers and oil exporters display a different dependency structure against the US dollar in the case of rising oil prices with the latter appreciating and the former depreciating.     

Common Stochastic Trends in a System of Exchange Rates

Univariate tests reveal strong evidence for the presence of a unit root in the univariate time-series representation for seven daily spot and forward exchange rate series. Furthermore, all seven spot and forward rates appear to be cointegrated; that is, the forward premiums are stationary, and one common unit root, or stochastic trend, is detectable in the multivariate time-series models for the seven spot and forward rates, respectively. This is consistent with the hypothesis that the seven exchange rates possess one long-run relationship and that the disequilibrium error around that relationship partly accounts for subsequent movements in the exchange rates.     

Beyond the purchasing power parity: testing for cointegration and causality between exchange rates, prices, and interest rates

This paper reexamines the causality between the dollar and the yen in a multivariate framework with the aid of cointegration and error-correcting modeling for the 1951–94 period. The Phillips-Perron tests and Johansen's tests are performed. While causality from interest rates to exchange rates is found in the short run, no causality between prices and exchange rates is found in the short run. However, causality is found running from relative prices to exchange rates along with interest rates between the U.S. and Japan in the long run, which supports the long-run PPP hypothesis.     

A Variance-Ratio Test of Random Walks in Foreign Exchange Rates

The separate variance-ratio tests under homoscedasticity and heteroscedasticity both provide evidence rejecting the random walk hypothesis, using five pairs of weekly nominal exchange rate series over the period from August 7, 1974 to March 29, 1989. The rejections cast doubt on the random walk hypothesis in exchange rates, which has received support in the existing literature. Furthermore, since the rejections are robust to heteroscedasticity, they suggest autocorelations of weekly increments in the nominal exchange rate series, which may be consistent with the exchange rate overshooting or undershooting phenomenon.     

Three‐Regime Asymmetric STAR Modeling and Exchange Rate Reversion

The breakdown of the Bretton Woods system and the adoption of generalized floating exchange rates ushered in a new era of exchange rate volatility and uncertainty. This increased volatility leads economists to search for economic models able to describe observed exchange rate behavior. In the present paper, we propose more general STAR transition functions that encompass both threshold nonlinearity and asymmetric effects. Our framework allows for a gradual adjustment from one regime to another and considers threshold effects by encompassing other existing models, such as TAR models. We apply our methodology to three different exchange rate data sets: one for developing countries and official nominal exchange rates, the second for emerging market economies using black market exchange rates, and the third for OECD economies.     

Does oil price have similar effects on the exchange rates of BRICS?

Motivated by the crucial status of oil price and exchange rates in world finance and economy, we apply daily data from August 2005 to February 2019 to investigate the impact of oil price shocks on the exchange rate of BRICS countries. This paper first adopts a new framework and EEMD method to decompose oil shocks and exchange rate series, respectively. With these econometric methods, the final research variables in this paper are constructed, including two types of oil shocks and three kinds of exchange rate series. The ARDL approach and VAR model are then employed to detect the influence of oil shocks on exchange rates in different frequencies, corresponding to the stationarity of series. The evidence, based on the original exchange rate series reveals that two oil price shocks can produce different effects on net oil-importing countries and net oil-exporting countries, while the results from different frequencies show that exchange rates will have a significant response to oil shocks only at a high frequency. It is worth noting that China is a unique case in BRICS, the relations between its exchange rate and oil price shocks is far insignificant than that of the other countries.