Temporal aggregation and purchasing power parity persistence

This paper uses a unique new monthly US-UK real exchange rate series for the January 1794-December 2009 period to reexamine the academic debate over purchasing power parity (PPP). The consensus view described by Rogoff (1996) is that PPP holds in the long-run, but short-run deviations are very persistent, with half-lives ranging from 3 to 5 years. Most of the literature using long time series relies on the annual data developed by Lee (1976) and Lothian and Taylor (1996), which were both constructed from underlying higher-frequency data sources. Estimates of purchasing power parity persistence using these series may therefore be subject to temporal aggregation bias. We find evidence of aggregation bias which indicates the half-life of PPP deviations has been overestimated in much of the previous literature. We also find that estimates of the half-lives are further reduced once we account for the Harrod (1933)-Balassa (1964)-Samuelson (1964) effect. The result of aggregation bias appears to be robust even when considering the case that real exchange rates exhibit nonlinear dynamics.     

The high-frequency response of exchange rates and interest rates to macroeconomic announcements

The joint movements of exchange rates and U.S. and foreign term structures over short-time windows around macro announcements are studied using a 14-year span of high-frequency data. In order to evaluate whether the joint effects can be reconciled with conventional theory, the implications of these joint movements for changes in expected future exchange rates and changes in foreign exchange risk premia are deduced. For several real macro announcements, a stronger than expected release appreciates the dollar today, and must either (i) lower the risk premium for holding foreign currency rather than dollars, or (ii) imply net expected dollar depreciation over the ensuing decade.     

On the sensitivity of the volume and volatility of bilateral trade flows to exchange rate uncertainty

We present an empirical investigation of the hypotheses that exchange rate uncertainty may have an impact on both the volume and variability of trade flows by considering a broad set of industrial countries' bilateral real trade flows over the period 1980–1998. Similar to the findings of earlier theoretical and empirical research, our first set of results shows that the impact of exchange rate uncertainty on trade flows is indeterminate. Our second set of results provides new and novel findings that exchange rate uncertainty has a consistent positive and significant effect on the volatility of bilateral trade flows, helping us better understand macroeconomic volatility.     

Mean and volatility dynamics of Indian rupee/US dollar exchange rate series: an empirical investigation

The paper is concerned with time series modelling of foreign exchange rate of an important emerging economy, viz., India, with due consideration to possible sources of misspecification of the conditional mean like serial correlation, parameter instability, omitted time series variables and nonlinear dependences. Since structural change is pervasive in economic time series relationships, the paper first studies this aspect of the exchange rate series in detail and finds the existence of four structural breaks. Accordingly, the entire sample period is divided into five sub-periods of stable parameters each, and then the appropriate mean specification for each of these sub-periods is determined by incorporating functions of recursive residuals. Thereafter, the GARCH and EGARCH models are considered to capture the volatility contained in the data. The estimated models thus obtained suggest that return on Indian exchange rate series is marked by instabilities and that the appropriate volatility model is EGARCH. Further, out-of-sample forecasting performance of the model has been studied by standard forecasting criteria, and then compared with that of an AR model only to find that the findings are quite favorable for the former.      

How well does nonlinear mean reversion solve the PPP puzzle?

This paper addresses the degree to which models which exhibit nonlinear mean reversion (NMR) present a resolution to the Purchasing Power Parity Puzzle. This paper develops a method of estimating a representative distribution of half lives which is based upon the observed distribution of shocks in a given time series rather than choosing shock sizes arbitrarily which is the current practice in the literature. This approach is implemented with data on five real exchange rates. The empirical analysis shows that half lives shorter than the consensus are observed frequently enough to support the proposition that NMR is a solution to the PPP puzzle.     

Estimating exchange rate responsiveness to shocks

The goal of this paper is to examine the importance of permanent and transitory shocks using a more efficient trend-cycle decomposition of the real exchange rate series. Our main contribution is that in measuring the impact of shocks, we not only impose common trend restrictions but also common cycle restrictions. We later confirm, through a post sample forecasting exercise, the efficiency gains from imposing common cycle restrictions. Our results indicate that permanent shocks are responsible for the bulk of the real exchange rate variations for Japan, Italy, Germany, France, and the UK vis-à-vis the US dollar over short horizons. For Canada, however, transitory shocks are dominant over the short horizon. In sum, while for Japan, France, and Italy, around 15% of the variation in real exchange rate is due to transitory shocks, for Canada, Germany and the UK, over 25% of the variations over the short horizon are due to transitory shocks. Thus, we claim that the role of transitory shocks should not be ignored.     

Long memory and nonlinearity in conditional variances: A smooth transition FIGARCH model

This paper introduces the Smooth Transition version of FIGARCH model which is designed to account for both long memory and nonlinear dynamics in the conditional variance. Nonlinearity is introduced via a logistic transition function. The model can capture smooth changes in the volatility across different regimes as well as asymmetric response to negative and positive shocks and allows for nonzero thresholds. Simulations find that the Smooth Transition FIGARCH model outperforms the standard FIGARCH model when nonlinearity is present, and ignoring nonlinearity in the data may induce considerable costs in terms of bias and efficiency. Applications to exchange rate and stock market data show that the proposed model performs well both in-sample fit as well as in forecasting one-day ahead volatility.     

A century of purchasing power parity confirmed: The role of nonlinearity

Taylor (2002) claims that Purchasing Power Parity (PPP) has held over the 20th century based on strong evidence of stationary for century-long real exchange rates for 20 countries. Lopez et al. (2005), however, found much weaker evidence of PPP with alternative lag selection methods. We reevaluate Taylor’s claim by implementing a recently developed nonlinear unit root test by Park and Shintani (2005). We find strong evidence of nonlinear mean-reversion in real exchange rates that confirms Taylor’s claim. We also find a possible misspecification problem in using the ESTAR model that may not be detected with Taylor-approximation based tests.     

Short-run forecasting of the euro-dollar exchange rate with economic fundamentals

We propose a fundamentals-based econometric model for the weekly changes in the euro-dollar rate with the distinctive feature of mixing economic variables quoted at different frequencies. The model obtains good in-sample fit and, more importantly, encouraging out-of-sample forecasting results at horizons ranging from one-week to one month. Specifically, we obtain statistically significant improvements upon the hard-to-beat random-walk model using traditional statistical measures of forecasting error at all horizons. Moreover, our model obtains a great improvement when we use the direction of change metric, which has more economic relevance than other loss measures. With this measure, our model performs much better at all forecasting horizons than a naive model that predicts the exchange rate as an equal chance to go up or down, with statistically significant improvements.     

Volatility clustering,leverage effects,and jump dynamics in the US and emerging Asian equity markets

This paper proposes asymmetric GARCH-Jump models that synthesize autoregressive jump intensities and volatility feedback in the jump component. Our results indicate that these models provide a better fit for the dynamics of the equity returns in the US and emerging Asian markets, irrespective whether the volatility feedback is generated through a common GARCH multiplier or a separate measure of volatility in the jump intensity function. We also find that they can capture several distinguishing features of the return dynamics in emerging markets, such as, more volatility persistence, less leverage effects, fatter tails, and greater contribution and variability of the jump component.     

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.     

Inflation Dynamics in the U.S.: Global but Not Local Mean Reversion

A stylized fact of U.S. inflation dynamics is one of extreme persistence and possible unit root behavior. If so, the implications for macroeconomics and monetary policy are somewhat unpalatable. Our econometric analysis proposes a parsimonious univariate representation of the inflation process for the last 60 years, the nonlinear exponential smooth autoregressive. The empirical results confirm a number of the key features such as global stationarity, local unit root behavior, and lower persistence in the post-1983 period than in the pre-1983 period. We compare the forecasting ability of our model with that of competing univariate models and find that the nonlinear model outperforms the linear autoregressive model in the pre-1983 period and the random walk in the post-1983 period at short horizons.     

Using self-organizing maps to adjust for intra-day seasonality

The existence of an intra-day seasonality component in financial market variables (volatility, volume, activity, etc.) has been highlighted in many previous studies. To remove this cyclical component from raw data, many researchers use the intra-day average observations model (IAOM) and/or some smoothing techniques (e.g. the kernel method). When the seasonality is related to the first moment (the conditional expectation) and involves only a deterministic component, the IAOM method succeeds in estimating the periodicity almost perfectly. However, when seasonality affects the first or the second moment (the conditional variance) of the data and contains both deterministic and stochastic components, both IAOM and the kernel method fail to capture it. We introduce self-organizing maps (SOM) as a solution. SOM are based on neural network learning and nonlinear projections. Their flexibility allows seasonality to be captured even in the presence of stochastic cycles.     

What drives volatility persistence in the foreign exchange market?

We propose a new empirical specification of volatility that links volatility to the information flow, measured as the order flow in the market, and to the price sensitivity to that information. The time-varying market sensitivity to information is estimated from high-frequency data, and movements in volatility can therefore be directly related to movements in order flow and market sensitivity. Empirically, the model explains a large share of the long-run variation in volatility. Importantly, the time variation in the market's sensitivity to information is at least as relevant in explaining the persistence of volatility as the rate of information arrival itself. This may be evidence of a link between changes over time in the aggregate behavior of market participants and the time-series properties of realized volatility.     

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.     

Impact of macro-economic surprises on carry trade activity

Can official news and policy announcements affect foreign exchange speculation? A widespread speculative strategy in foreign exchange markets is carry trade. This paper explores the links between macro-economic news and foreign exchange options to identify macro-economic fundamentals most relevant to the pricing of downside risk – measured by risk reversals options contracts – to carry trade activity. Focusing primarily on the Japanese yen carry trade, we identify a significant impact of macro-economic surprises on dollar/yen risk reversals. The effect is sizeable, with news related to bilateral trade balance of particular concern. Moreover, there is a close link between risk reversals and speculative futures positions in Japanese yen. This allows us to quantify a substantial effect of macro-economic news on carry trade activity, with the cost of hedging as the transmission mechanism.     

Foreign exchange,fractional cointegration and the implied–realized volatility relation

Almost all relevant literature has characterized implied volatility as a biased predictor of realized volatility. In this paper we provide new time series techniques to investigate the validity of this finding in several foreign exchange options markets, including the Euro market. First, we develop a new fractional cointegration test that is shown to be robust to both stationary and non-stationary regions. Second, we employ both intra-day and daily data to measure realized volatility in order to assess the relevance of data frequency in resolving the bias. Third, we use data on implied volatility traded on the market. In contrast to previous studies, we show that the frequency of data used for measuring realized volatility within a fractionally cointegrating framework is important for the results of unbiasedness tests. Significantly, for many popular exchange rates, the use of intra-day rather than daily data affects the emergence of a different bias, as the possibility of a fractionally integrated risk premium admits itself!     

Does the forward premium puzzle disappear over the horizon?

This paper provides the first comprehensive study of the horizon effect in tests of the forward rate unbiasedness hypothesis. It estimates Fama regressions employing 1-month through to 10-year horizon data for the five most heavily traded US dollar currency pairs pre-crisis 1980–2006. In contrast with extant studies, it fully deals with the econometric problems of long horizon regressions by means of a novel heteroskedastic- and autocorrelation-consistent bootstrap. The regression results confirm a clear horizon effect in that the slope coefficient approaches unity as the forward contract maturity is extended. The puzzle disappears at the 3-year horizon and beyond for all currencies.     

Bivariate relative city price convergence in the United States: 1918-1997

As in international tests of purchasing power parity, panel unit root tests have been successful in rejecting a unit root process in U.S. city relative prices over the period 1918-1997. However, there is an empirical question of what the rejection of a ‘panel unit root’, particularly with respect to real exchange rates, means. This paper employs a variety of univariate unit root and cointegration tests which have recently come to the fore. These tests improve the power and reduce size distortion found in standard unit root and cointegration tests such as the Dickey-Fuller and Phillips-Perron tests. I find considerable evidence for rejecting a unit root process in the majority of U.S. city relative prices over the entire sample period and two subperiods. Less successful are stationarity tests conducted on regions of the U.S.     

Expectations of future income and real exchange rate movements

We show that changes in expectations of future income driven by exogenous factors (such as the discovery of oil and an increase in global demand for natural resources) can cause movements in the real exchange rate (RER) in excess of, and sometimes even in the opposite direction to, what one would expect given the changes in current income. We provide both a theoretical model and empirical evidence of this. In particular, we show that the signing of numerous production sharing agreements (PSAs) between the government of Azerbaijan and foreign oil companies in 1994–1998 fueled expectations of higher future incomes, resulting in a considerable appreciation of the RER. Some of these PSAs subsequently failed or ran into difficulties, which led to a downward revision of expected future income and a depreciation of the RER in 1999–2003, even though the current income started to rise, due to an increase in the current oil revenue.