Modelling economic high-frequency time series with STAR-STGARCH models

In this paper we introduce the STAR-STGARCH model that can characterize nonlinear behaviour both in the conditional mean and the conditional variance. A modelling cycle for this family of models, consisting of specification, estimation, and evaluation stages is constructed. Misspecification tests for the estimated model are obtained using standard asymptotic distribution theory. We illustrate the actual modelling by applying the STAR-STGARCH model family to two series of daily observations, the Swedish OMX index and the exchange rate JPY-USD.Financial time series; model misspecification test; nonlinear time series; smooth transition autoregressive model; smooth transition GARCH; time series model specification.

Developments in European Pension Regulation: Risks and Challenges

The paper will discuss the proposed regulatory frameworks (market valuation of liabilities) in Europe and the implications it will have on pension provision. The impact on current DB pension schemes and insured solutions with guarantees will be discussed in detail especially on the sustainability of the current guaranteed products. Collective solutions that are capital efficient under the proposed regulatory framework will be outlined as a viable alternative to Individual DC

A flexible approach to parametric inference in nonlinear and time varying time series models

Many structural break and regime-switching models have been used with macroeconomic and …nancial data. In this paper, we develop an extremely flexible parametric model which can accommodate virtually any of these speci…cations and does so in a simple way which allows for straightforward Bayesian inference. The basic idea underlying our model is that it adds two simple concepts to a standard state space framework. These ideas are ordering and distance. By ordering the data in various ways, we can accommodate a wide variety of nonlinear time series models, including those with regime-switching and structural breaks. By allowing the state equation variances to depend on the distance between observations, the parameters can evolve in a wide variety of ways, allowing for everything from models exhibiting abrupt change (e.g. threshold autoregressive models or standard structural break models) to those which allow for a gradual evolution of parameters (e.g. smooth transition autoregressive models or time varying parameter models). We show how our model will (approximately) nest virtually every popular model in the regime-switching and structural break literatures. Bayesian econometric methods for inference in this model are developed. Because we stay within a state space framework, these methods are relatively straightforward, drawing on the existing literature. We use arti…cial data to show the advantages of our approach, before providing two empirical illustrations involving the modeling of real GDP growth

A review of the pesticide MCPA in the land-water environment and emerging research needs

peer-reviewedDue to its high solubility and poor adsorption to the soil matrix, the postemergence herbicide 2-methyl-4-chlorophenoxyacetic acid (MCPA) is susceptible to transport into surface and groundwater bodies, where it can result in compromised water quality and breaches of legislative standards. However, there is still poor understanding of catchment scale dynamics and transport, particularly across heterogeneous hydrogeological settings. While it is known that MCPA degrades under aerobic conditions, negligible breakdown can occur in anaerobic environments, potentially creating a legacy in saturated soils. Fast runoff pathways post application are likely transport routes, but the relative contribution from the mobilization of legacy MCPA from anaerobic zones has yet to be quantified, making the delineation of MCPA sources encountered during monitoring programs challenging. While ecotoxicological effects have been examined, little is known about the interaction of MCPA (and its degradation products) with other pesticides, with nutrients or with colloids, and how this combines with environmental conditions to contribute to multiple stressor effects. We examine the state of MCPA knowledge, using case study examples from Ireland, and consider the implications of its widespread detection in waterbodies and drinking water supplies. Research themes required to ensure the sustainable and safe use of MCPA in an evolving agricultural, social and political landscape are identified here. These include the need to identify mitigation measures and/or alternative treatments, to gain insights into the conditions governing mobilization and attenuation, to map pathways of migration and to identify direct, synergistic and antagonistic ecotoxicological effects

Dynamic asymmetries in house price cycles: A generalized smooth transition model

In this paper we propose a novel nonlinear model to capture asymmetries in real estate cycles. The approach involves a particular parametrization of the transition function used in the transition equation of a smooth transition autoregressive model which improves the fit in the non-central probability region. The dynamic symmetry in house price cycles is strongly rejected for the housing markets taken into consideration. Further, our results show that the proposed model performs well in a out of sample forecasting exercise

Detecting Mutiple Breaks in Financial Market Volatility Dynamics

Nous appliquons plusieurs nouveaux tests conçus pour déceler les ruptures structurelles dans la dynamique de variance et de covariance conditionnelles. Les tests s'appliquent à la fois aux processus de la classe ARCH et de type SV et tiennent compte des caractéristiques de mémoire longue. Nous les appliquons également aux estimateurs de volatilité engendrés par les données, en utilisant des données à haute fréquence et nous suggérons des applications multivariées. En plus de déterminer la présence des ruptures, les statistiques permettent d identifier le nombre de ruptures ainsi que l'emplacement de ruptures multiples. Nous étudions la taille et la puissance des nouveaux tests pour divers modèles réalistes univariés et multivariés de variance conditionnelle et d échantillonnage. L article conclut avec une analyse empirique à partir de données provenant des marchés d actions et de taux de change pour lesquels nous trouvons de multiples ruptures associées aux crises financières asiatiques et russes. Dans les échantillons sélectionnés avant et après les ruptures, nous trouvons des changements dans la dynamique et dans la mémoire longue de la volatilité.We apply several recently proposed tests for structural breaks in conditional variance and covariance dynamics. The tests apply to both the class of ARCH and SV type processes and allow for long memory features. We also apply them to data-driven volatility estimators using high-frequency data and suggest multivariate applications. In addition to testing for the presence of breaks, the statistics allow to identify the number of breaks and the location of multiple breaks. We study the size and power of the new tests under various realistic univariate and multivariate conditional variance models and sampling schemes. The paper concludes with an empirical analysis using data from the stock and FX markets for which we find multiple breaks associated with the Asian and Russian financial crises. We find changes in the dynamics and long memory of volatility in the samples prior and post the breaks

Economic Crisis and Investor Behaviour

This study investigates the effects of crises on domestic and foreign investors’ behaviours by utilizing a nonlinear approach. Considering the nonlinearity inherent in many financial variables, this study proposes an appropriate econometric modelling for analysing the investors’ behaviour, particularly during turbulent times. Specifically, STAR-STGARCH family models and generalized impulse response function analysis (GIRF) are employed to understand the different reactions of foreign and domestic investors at the Malaysian Stock Exchange market during the 1997 Asian crisis. The results of the model and the GIRF analysis have shown that foreign investors exhibited a herding behavior during the crisis and responded the shock more quickly than the domestic investors. When the same analysis is applied to understand the effects of the 2008 Subprime Mortgage Crisis in the Malaysian market, the behaviors of foreign and domestic investors are found to be very similar

Norming rates and limit theory for some time-varying coefficient autoregressions

A time-varying autoregression is considered with a similarity-based coefficient and possible drift. It is shown that the random walk model has a natural interpretation as the leading term in a small-sigma expansion of a similarity model with an exponential similarity function as its autoregressive coefficient. Consistency of the quasi-maximum likelihood estimator of the parameters in this model is established, the behaviors of the score and Hessian functions are analyzed and test statistics are suggested. A complete list is provided of the normalization rates required for the consistency proof and for the score and Hessian functions standardization. A large family of unit root models with stationary and explosive alternatives are characterized within the similarity class through the asymptotic negligibility of a certain quadratic form that appears in the score function. A variant of the stochastic unit root model within the class is studied and a large sample limit theory provided which leads to a new nonlinear diffusion process limit showing the form of the drift and conditional volatility induce