On trend extraction models: Interpretation,empirical evidence and forecasting performance

This paper deals with the economic interpretation of the unobserved components model in the light of the apparent problem posed by previous work in that several practiced methodologies seem to lead to very different models of certain economic variables. A detailed empirical analysis is carried out to show how the failure in obtaining quasi-orthogonal components can seriously bias the interpretation of some decomposition procedures. Finally, the forecasting performance (in both the short and long run) of these decomposition models is analyzed in comparison with other alternatives.     

Signal extraction and estimation of a trend: a Monte Carlo study

Several authors (King and Rebelo, 1993; Cogley and Nason, 1995) have questioned the use of exponentially weighted moving average filters such as the Hodrick–Prescott filter in decomposing a series into a trend and cycle, claiming that they lead to the observation of spurious or induced cycles and to misinterpretation of stylized facts. However, little has been done to propose different methods of estimation or other ways of defining trend extraction. This paper has two main contributions. First, we suggest that the decomposition between the trend and cycle has not been done in an appropriate way. Second, we argue for a general to specific approach based on a more general filter, the stochastic trend model, that allows us to estimate all the parameters of the model rather than fixing them arbitrarily, as is done with mainly of the commonly used filters. We illustrate the properties of the proposed technique relative to the conventional ones by employing a Monte Carlo study. Copyright © 1999 John Wiley & Sons, Ltd.     

Comments on papers by Sharlin and Wall

Wall is convincing on the Fuller court, but less so on Holmes, who may have understood Spencer's Social statics as a laissez faire rather than as a Darwinist document. Sharlin helps us to follow Spencer's attempt to universalize the concept of energy, even if Sharlin's explanation for Spencer's failure reduces to an application of the classical insight that physical phenomena are more predictable than social phenomena. Sharlin's conception of ‘scientism’ is helpful in some contexts, but less so in others; we need to remind ourselves that the role of values in scientism is active as well as passive.     

On a family of finite moving‐average trend filters for the ends of series

A family of finite end filters is constructed using a minimum revisions criterion and based on a local dynamic model operating within the span of a given finite central filter. These end filters are equivalent to evaluating the central filter with unavailable future observations replaced by constrained optimal linear predictions. Two prediction methods are considered: best linear unbiased prediction and best linear biased prediction where the bias is time invariant. The properties of these end filters are determined. In particular, they are compared to X‐11 end filters and to the case where the central filter is evaluated with unavailable future observations predicted by global ARIMA models as in X‐11‐ARIMA or X‐12‐ARIMA. Copyright © 2002 John Wiley & Sons, Ltd.     

Saving the Strong Programme: a critique of Stephen Kemp’s recent paper

In this paper I intend to discuss some of the views put forward by Stephen Kemp in his recent critique of the Strong Program (Kemp, 2005). In particular I will try to defend David Bloor’s SSK against the charge of weak idealism brought up by Stephen Kemp in his paper. The widely held accusation, namely, according to which the social constructionist approach to scientific knowledge is strongly idealist, is already rejected by Kemp himself. He argues, however that Bloor’s attempts to divert the charge of idealism from the Strong Programme were not successful with respect to the kind of idealism that Kemp calls ‘weak idealism’, that is, treating scientific discourse as free-floating and unrelated to the world of things. I intend to argue that Kemp’s charges are unfounded when levelled at Bloor’s views on meaning and reference. Kemp deals with two issues of the Bloorian program: with the social constructionist approach to concepts as self-referential social institutions, and with the actor/analyst distinction introduced by the Strong Programmers. I will focus only on the first issue in my paper.     

Forecasting and trading strategies based on a price trend model

In this paper, we consider the price trend model in which it is assumed that the time series of a security's prices contain a stochastic trend component which remains constant on each of a sequence of time intervals, with each interval having random duration. A quasi‐maximum likelihood method is used to estimate the model parameters. Optimal one‐step‐ahead forecasts of returns are derived. The trading rule based on these forecasts is constructed and is found to bear similarity to a popular trading rule based on moving averages. When applying the methods to forecast the returns of the Hang Seng Index Futures in Hong Kong, we find that the performance of the newly developed trading rule is satisfactory. Copyright © 2000 John Wiley & Sons, Ltd.     

The performance of non‐linear exchange rate models: a forecasting comparison

In recent years there has been a considerable development in modelling non‐linearities and asymmetries in economic and financial variables. The aim of the current paper is to compare the forecasting performance of different models for the returns of three of the most traded exchange rates in terms of the US dollar, namely the French franc (FF/$), the German mark (DM/$) and the Japanese yen (Y/$). The relative performance of non‐linear models of the SETAR, STAR and GARCH types is contrasted with their linear counterparts. The results show that if attention is restricted to mean square forecast errors, the performance of the models, when distinguishable, tends to favour the linear models. The forecast performance of the models is evaluated also conditional on the regime at the forecast origin and on density forecasts. This analysis produces more evidence of forecasting gains from non‐linear models. Copyright © 2002 John Wiley & Sons, Ltd.     

Forecasting using high‐frequency data: a comparison of asymmetric financial duration models

The first purpose of this paper is to assess the short‐run forecasting capabilities of two competing financial duration models. The forecast performance of the Autoregressive Conditional Multinomial–Autoregressive Conditional Duration (ACM‐ACD) model is better than the Asymmetric Autoregressive Conditional Duration (AACD) model. However, the ACM‐ACD model is more complex in terms of the computational setting and is more sensitive to starting values. The second purpose is to examine the effects of market microstructure on the forecasting performance of the two models. The results indicate that the forecast performance of the models generally decreases as the liquidity of the stock increases, with the exception of the most liquid stocks. Furthermore, a simple filter of the raw data improves the performance of both models. Finally, the results suggest that both models capture the characteristics of the micro data very well with a minimum sample length of 20 days. Copyright © 2008 John Wiley & Sons, Ltd.     

Evaluating predictive performance of value‐at‐risk models in emerging markets: a reality check

We investigate the predictive performance of various classes of value‐at‐risk (VaR) models in several dimensions—unfiltered versus filtered VaR models, parametric versus nonparametric distributions, conventional versus extreme value distributions, and quantile regression versus inverting the conditional distribution function. By using the reality check test of White (2000), we compare the predictive power of alternative VaR models in terms of the empirical coverage probability and the predictive quantile loss for the stock markets of five Asian economies that suffered from the 1997–1998 financial crisis. The results based on these two criteria are largely compatible and indicate some empirical regularities of risk forecasts. The Riskmetrics model behaves reasonably well in tranquil periods, while some extreme value theory (EVT)‐based models do better in the crisis period. Filtering often appears to be useful for some models, particularly for the EVT models, though it could be harmful for some other models. The CaViaR quantile regression models of Engle and Manganelli (2004) have shown some success in predicting the VaR risk measure for various periods, generally more stable than those that invert a distribution function. Overall, the forecasting performance of the VaR models considered varies over the three periods before, during and after the crisis. Copyright © 2006 John Wiley & Sons, Ltd.     

Forecasting regional house price inflation: a comparison between dynamic factor models and vector autoregressive models

This paper uses the dynamic factor model framework, which accommodates a large cross‐section of macroeconomic time series, for forecasting regional house price inflation. In this study, we forecast house price inflation for five metropolitan areas of South Africa using principal components obtained from 282 quarterly macroeconomic time series in the period 1980:1 to 2006:4. The results, based on the root mean square errors of one to four quarters ahead out‐of‐sample forecasts over the period 2001:1 to 2006:4 indicate that, in the majority of the cases, the Dynamic Factor Model statistically outperforms the vector autoregressive models, using both the classical and the Bayesian treatments. We also consider spatial and non‐spatial specifications. Our results indicate that macroeconomic fundamentals in forecasting house price inflation are important. Copyright © 2010 John Wiley & Sons, Ltd.     

Computational models: a modest role for content

The computational theory of mind construes the mind as an information-processor and cognitive capacities as essentially representational capacities. Proponents of the view (hereafter, ‘computationalists’) claim a central role for representational content in computational models of these capacities. In this paper I argue that the standard view of the role of representational content in computational models is mistaken; I argue that representational content is to be understood as a gloss on the computational characterization of a cognitive process.     

Detection of dipeptides and dipeptidase activity on paper

Riassunto Viene descritto un metodo rapido e sensibile per la rilevazione delle dipeptidasi su carta.