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In what seems as an infinitely ongoing debate regarding the purchasing power parity (PPP) theory, this paper seeks to question the strength of the scientific “evidence” put forward by the PPP revisionists

In this paper, the validity of the PPP revisionists' scientific evidence supporting long‐run PPP is questioned based on the replication of an influential review study that is considered by PPP revisionists to exhibit “some of the strongest evidence” in favour of the PPP theory.

By simulation experiments it is demonstrated that the traditional PPP unit root tests are non‐robust to the empirically identified (G)ARCH distortions. Due to (G)ARCH distortions, over‐rejections for the traditional unit root tests are shown to be a problem that potentially misleads researchers to believe that long‐run PPP holds under circumstances when it is in fact not valid. As a potential remedy to this problem, a new unit root test is introduced which is robust to conditional heteroscedasticity disturbances, and in contrast to traditional unit root tests, it exhibits no significant empirical support for the PPP theory.

The study illustrates that the PPP revisionists' unit root tests cannot reliably test the PPP hypothesis in the presence of (G)ARCH distortions, due to bad power and size properties. Perhaps it is time to conclude that, based on the currently existing research, it is virtually impossible to empirically come to a credible conclusion regarding whether long‐run PPP holds or not.

The purpose of this paper is to test for and model non‐linearities in option price deviations from the Black Scholes (BS) model in FTSE 100 index options over the time period 1997‐2006.

The economic specification and estimation methodology is outlined, the data are discussed, and the empirical results are analysed.

The tests reject the linearity hypothesis and the paper shows that the exponential smooth transition autoregressive model is capable of capturing the non‐linear behaviour of option price misalignments. The paper finds that even though FTSE 100 index options are heavily traded, transaction costs prevent rapid adjustments of option prices from their “optimal” value.

The paper presents new empirical evidence, which explicitly allows for the possibility that option price misalignments from the BS price can be characterised by a non‐linear mean reverting process.

The purpose of this paper is to investigate the validity of the cost of carry model by examining the time series properties of the deviation between future and spot prices in the European Union Emissions Trading Scheme (EU-ETS) over the time period 2005-2012. The paper utilizes a non-linear mean reverting adjustment mechanism, and discovers that although deviations of future from spot prices can exhibit a region of non-stationary behaviour, overall they are stationary indicating market efficiency in the trading of carbon permits.

The methodology involves non-linear mean reverting unit root tests.

The findings provide insights into the functioning of the EU-ETS market. They suggest that it is informationally efficient and does not permit arbitrage between spots and futures.

The authors are the first study to examine efficiency in the EU-ETS by investigating the validity of the cost of carry model. The authors are also the only study to look at efficiency in both Phase I and Phase II of the scheme.

The aim of this paper is to model the dynamic path of adjustment towards pre‐unemployment levels of wellbeing for a group of full‐time workers who experienced job loss.

Based on data from the German Socio‐economic Panel, a large‐scale panel survey, the paper captures the non‐linear nature of the adaptation process by using an Exponential Smooth Transition Autoregressive (ESTAR) model.

The study finds that adaptation takes place in a non‐linear fashion, with the speed of adjustment being higher for high earners, those with high pre‐unemployment levels of life satisfaction and those who were most satisfied with their jobs before becoming unemployed. It also finds that most of the adaptation takes place during the first year of unemployment, with adaptation speeds decreasing with unemployment duration, suggestive of possible habituation effects being present.

This is the first study to model the dynamic path of adjustment towards pre‐unemployment wellbeing levels as a non‐linear process. Despite the challenge posed by adaptation theory and the recent interest in the wellbeing effects of job loss, there is only sparse empirical evidence on the dynamics of the adaptation to unemployment process.

This paper aims to examine asymmetries in the house price cycle and to understand the dynamic of housing prices, incorporating macroeconomic variables at regional and country level, namely, housing affordability, the unemployment rate, mortgage rate and inflation rate.

To highlight significant differences in the asymmetric patterns of house prices between regions, the STAR model is adopted.

The authors highlight significant differences in the asymmetric patterns of house prices between regions, in which some areas showed asymmetric response over the housing cycle; here the LSTAR model outperforms other models. In contrast, some regions (the South West and the North West) showed symmetric properties in the tails of the cycle; therefore, the ESTAR model was adopted in their case.

Being limited to a few fundamentals, this study opens an avenue for further research to investigate this dynamic using in addition such demand-supply factors as land supply, construction cost and loans made for housing. These findings can also be used to examine whether other models such as ARIMA, exponential smoothing or artificial neural networks can more accurately forecast housing prices.

The present paper aims to highlight housing affordability as a cause of asymmetric behaviour in house prices. Put differently, the authors seek to understand the dynamics of housing prices with other fundamentals incorporating macroeconomic variables in regions and country level data as a means of achieving a more concise result.

The purpose of this paper is to test and model non-linearities in block price deviations when they are executed outside the bid-ask quotes. The author conducts an empirical analysis on 662,312 transactions that were traded outside the bid-ask quotes in 2014 on the London Stock Exchange.

The tests reject the linearity hypothesis and the paper shows that the exponential smooth transition autoregressive model is capable of capturing the non-linear behaviour of block price misalignments.

The findings imply that when the deviation of block prices from their quoted value is small (large), trading will occur slowly (rapidly) to restore equilibrium, suggesting that trading costs eliminate continuous trading and that the block trade market is efficient.

The purpose of this paper is to re-model block price deviations from the bid-ask quotes. The major contribution is that the paper presents new empirical evidence, which explicitly allows for the possibility that block price misalignments from the bid-ask quotes can be characterized by a non-linear mean reverting process. The author demonstrates that the presence of transaction costs induces non-linear adjustments of block trade prices.

This paper aims to examine two hypotheses that have not been well investigated in the existing literature. One hypothesis is that the real interest rates of industrial countries tend to be mean‐reverting during the current floating exchange rate period. Another hypothesis is that the real interest rates of the countries involved in forming the Euro area are more likely to behave as nonlinear stationary series than those of other industrial countries.

The study applies the conventional linear unit root tests and recently developed nonlinear unit root tests, as well as the tests of specifying nonlinearity in time series, to the short‐term real interest rates of 16 industrial countries.

The results of the study provide support for both hypotheses.

The results imply that, having adopted target‐zone type stabilization policies for years, the central banks of European Monetary Union (EMU) countries were likely to have exercised monetary policies in a nonlinear way, especially in the process of meeting the requirements of joining EMU.

The study provides stronger evidence than previous studies for the theory that real interest rates of industrial countries tend to have mean‐reverting behavior. The study suggests that more active monetary policies for inflation control in the floating exchange rate period may have enhanced mean reversion in real interest rates.

The aim of this chapter is to assess the real exchange rate misalignments. A smooth transition autoregressive model (STAR) is used for Tunisian exchange market. This model allows us to see whether these differences are temporary or persistent over the period 1975–2012. We start by defining the exchange rate’s fundamental determinants to provide the equilibrium exchange rate value. Then, we study the observed exchange rate adjustment toward its equilibrium level. Vector autoregressive model and vector error correction model are applied to characterize the joint dynamics of variables in the long run. The results indicate a long-run relationship between variables. In order to consider the nonlinearity for better results, we will move to nonlinear smooth transition model. We found there is a high degree of exchange rate misalignment. We recognized that this difference decreases in the long run and disappears at the end.

The purpose of this paper is to expand on the sparse literature on non-linear modelling in South Africa and test for non-linearity of the market cycle on the Johannesburg Stock Exchange, with specific focus on a particular non-linear model – a Smooth Transition Auto-Regressive (STAR) model.

Non-linear estimation methods are used to describe the market cycle, as defined by equity prices, for the period 1998-2010.

In applying the STAR model to daily, weekly and monthly returns data, it was found that the fit of this family of models differs heavily based on the frequency of data used. The daily Logarithmic STAR (LSTAR) model was found to be the best fit relative to other data frequencies. Indeed, the weekly LSTAR model, while still appropriate to use, was less apt at forecasting than its daily counterpart. Monthly return data indicated that a linear AR model was more appropriate than a non-linear one.

The results assist in understanding the cyclical nature of emerging markets as well contributing to the understanding of creating a portfolio consisting of international securities. If one can show that equity returns in a particular emerging market follow non-linear behaviour, expanding this hypothesis to other emerging markets enables a minimum variance portfolio to be constructed that is informed by returns changing over time.

The findings can be used for further research into share price modelling, portfolio management and perhaps as an avenue into the reasoning behind the formation of market cycles.

This survey focuses on two families of nonlinear vector time series models, the family of vector threshold regression (VTR) models and that of vector smooth transition regression (VSTR) models. These two model classes contain incomplete models in the sense that strongly exogeneous variables are allowed in the equations. The emphasis is on stationary models, but the considerations also include nonstationary VTR and VSTR models with cointegrated variables. Model specification, estimation and evaluation is considered, and the use of the models illustrated by macroeconomic examples from the literature.