Modelling and trading the EUR/USD exchange rate at the ECB fixing

The motivation for this paper is to investigate the use of alternative novel neural network (NN) architectures when applied to the task of forecasting and trading the euro/dollar (EUR/USD) exchange rate, using the European Central Bank (ECB) fixing series with only auto-regressive terms as inputs. This is done by benchmarking four different NN designs representing a higher-order neural network (HONN), a Psi Sigma Network and a recurrent neural network with the classic multilayer perception (MLP) and some traditional techniques, either statistical such as an auto-regressive moving average model, or technical such as a moving average convergence/divergence model, plus a naïve strategy. More specifically, the trading performance of all models is investigated in a forecast and trading simulation on the EUR/USD ECB fixing time series over the period 1999–2007 using the last one and half years for out-of-sample testing, an original feature of this paper. We use the EUR/USD daily fixing by the ECB as many financial institutions are ready to trade at this level and it is therefore possible to leave orders with a bank for business to be transacted on that basis. As it turns out, the MLP does remarkably well and outperforms all other models in a simple trading simulation exercise. However, when more sophisticated trading strategies using confirmation filters and leverage are applied, the HONN network produces better results and outperforms all other NN and traditional statistical models in terms of annualized return.     

A comparison of statistical tests for the adequacy of a neural network regression model

An integral part of econometric practice is to test the adequacy of model specifications. If a model is adequately specified, it should not leave interesting features of the data-generating process in the errors. Despite the common tradition, the importance of diagnostic checking as a safeguard against mis-specification has only recently been recognized by neural network (NN) practitioners, possibly because this type of semi-parametric methodology was not originally designed for economic and financial applications. The purpose of this paper is to compare a number of analytical statistical testing procedures suitable to diagnostic checking on a neural network regression model. We present the standard Lagrange multiplier (LM) testing framework designed under the assumption of identically distributed disturbances and also examine two modifications that are robust to heteroskedasticity in errors. One modification also gives the researcher an opportunity to incorporate information concerning the volatility structure of the data-generating process in the testing procedure. By means of a Monte Carlo simulation, we investigate the performance of these tests under GARCH-type heteroskedasticity in errors and various distributional assumptions. The results show that although the primary concern of the researcher may be to design a regression model that accurately captures relations in the mean of the conditional distribution, developing a good approximation of the underlying volatility structure generally increases the efficiency of tests in detecting non-adequacy of a NN model.     

New development: Managing and accounting for sustainable development across generations in public services—and call for papers

Social and environmental justice across generations is a fundamental attribute of sustainable development. In this article, which is also a call for papers for a future theme in Public Money & Management (PMM), we develop our case for further research on how governments and public service organizations seek to address sustainable development in their decision-making processes. We believe that accounting for social and environmental aspects is an underdeveloped area of research and practice that is worthy of further critical enquiry. We therefore call on researchers and practitioners to submit their research to a themed issue of PMM on managing and accounting for sustainable development in public services.     

Broadband business by utilities infrastructure exploitation: A multistage competition model

A promising broadband business opportunity is the exploitation of the physical resources owned by municipalities and utility-based firms. In this study, the new broadband business opportunities owned by these authorities are analyzed through the development of a decision analysis model. The proposed model analyzes the broadband business into stages, integrates real options and game theory and provides business equilibrium in terms of the time of entry in the market, quantity offer and price definition. Finally, a real world case study is discussed showing how the model can be applied.     

Stock market prediction using evolutionary support vector machines: an application to the ASE20 index

The main motivation for this paper is to introduce a novel hybrid method for the prediction of the directional movement of financial assets with an application to the ASE20 Greek stock index. Specifically, we use an alternative computational methodology named evolutionary support vector machine (ESVM) stock predictor for modeling and trading the ASE20 Greek stock index extending the universe of the examined inputs to include autoregressive inputs and moving averages of the ASE20 index and other four financial indices. The proposed hybrid method consists of a combination of genetic algorithms with support vector machines modified to uncover effective short-term trading models and overcome the limitations of existing methods. For comparison purposes, the trading performance of the ESVM stock predictor is benchmarked with four traditional strategies (a naïve strategy, a buy and hold strategy, a moving average convergence/divergence and an autoregressive moving average model), and a multilayer perceptron neural network model. As it turns out, the proposed methodology produces a higher trading performance, even during the financial crisis period, in terms of annualized return and information ratio, while providing information about the relationship between the ASE20 index and DAX30, NIKKEI225, FTSE100 and S&P500 indices.     

Exchange rate determination: Empirical evidence for the Greek drachma

We examine the monetary approach to the exchange rate from several perspectives, using monthly data on five Greek bilateral exchange rates. Using the Johansen multivariate cointegration technique we demonstrate that the monetary model is validate as a long-run relationship. Moreover, upon imposing the long-run monetary model restrictions we find that the proportionality of the exchange rate to relative monetary aggregates is accepted for the bilateral exchange rate of the Greek drachma with respect to the US dollar, the deutschemark, the pound sterling, the French franc and the Italian lira. Finally, using the Hansen-Johansen (1993) testing procedure, we reject the hypothesis of sample independency of the dimension of the cointegration space in all cases, apart from the German one, but we accept the hypothesis that the estimated coefficients do not display instabilities in recursive estimations.     

Capital outflow liberalization and stock market reaction in an emerging market: Experience from Greece

This paper examines the response of the Greek equities market to the liberalization of capital flows during the 1992–1994 period. While past empirical research has largely examined the effects of capital inflow liberalization in emerging markets, we focus on capital outflow liberalization. In particular, we consider changes in the regulatory environment that allow domestic investors to hold foreign risky assets. Employing a time series of daily equity returns, a wealth effect is found that is indirectly linked to the announcement of capital flow liberalization. Additionally, our results reveal a significant change in the daily return distribution before and after final implementation. The views expressed in this paper are solely those of the authors and should not be interpreted as those of their respective affiliations.     

Location and Survival of New Entry

Drawing from two different strands of literature, industrial ecology and spatial analysis, the paper attempts to examine the role that location plays in determining firm survival. A time-varying covariates hazard model is used on Greek firms, which enter manufacturing in the early 1980s and are followed up to 1992. Location in Greater Athens vs. the rest of the country affects survival positively, especially when smaller firms are concerned. Other firm variables such as current size, profitability, leverage and capital together with growth and industry contestability are also found to affect survival, which becomes more difficult for firms established closer to recessions.     

Foreign vs domestic ownership on debt reduction: An investigation of acquisition targets in Italy and Spain

This paper examines the role of foreign versus domestic ownership in reducing the debt levels of acquired firms in Italy and Spain over the period 2002–2010. Acknowledging that lower debt levels can mitigate the risk of failure and thus enhance the chances for a positive post-acquisition performance and survival, we particularly examine the causal effect of foreign and domestic acquisitions on two firm-level debt measures: gearing and short-term leverage. To estimate causal relationships, we control for selection bias by applying propensity score matching techniques. Our results indicate that foreign acquisition leads to a significant and steady reduction in the debt ratios of the target companies. In contrast, the relationship between domestic acquisition and debt reduction appears to be smaller and statistically less robust.     

The Hong Kong Umbrella Movement as a non-profit organization: An empirical study on the use of visual branding practices for social change

In this article, we draw our attention to the growth of a new social movement, as a non-profit organization which aims to effectively communicate its collective identity and messages to larger audiences. Initially, we provide a critical discussion on the interrelationships between marketing theory/practice and protest groups' promotional tactics. Afterwards, we focus on the interface between visual branding practices and new social movement's strategies to create a visual branding identity around their protest symbols and aims. In order to do so, we adopted a moderate participant observation approach to explore how the 2014 Hong Kong Umbrella Movement employed forms of visual branding to engage local and global audiences and induce social change. Drawing on a close examination of field notes and a visual analysis of digital archives and images from the protest sites, we identify and discuss the presence of several visual branding techniques for the imaginative promotion of the movement's demands and causes. Our findings suggest that the 2014 Umbrella Movement protesters coordinated and acted as non-profit organization which employed innovative and creative visual branding methods to enhance the movement's unity and trigger emotional responses from diverse audiences. We conclude the article with suggestions for future research around the interrelationships between social movements' protest symbols, transnational visual branding practices and non-profit organizational practices.