On the forecast accuracy and consistency of exchange rate expectations: The Spanish PwC Survey.

We examine the predictive ability and consistency properties of exchange rate expectations for the dollar/euro using a survey conducted in Spain by PwC among a panel of experts and entrepreneurs. Our results suggest that the PwC panel have some forecasting ability for time horizons from 3 to 9 months, although only for the 3-month ahead expectations we obtain marginal evidence of unbiasedness and efficiency in the forecasts. As for the consistency properties of the exchange rate expectations formation process, we find that survey participants form stabilising expectations in the short-run and destabilising expectations in the long- run and that the expectation formation process is closer to fundamentalists than chartists.

Modelos de desarrollo y sistemas de gestión pública: el SNIP peruano, 2000-2014

Esta Tesis tiene dos partes. La Primera Parte es Teórica y Metodológica y trata de la actual crisis de paradigma en las Ciencias Sociales, y de cómo se puede remontar con la Teoría del Pensamiento Complejo, siempre que sus propuestas se centren en modelos empíricos de Análisis de Redes Sociales debidamente matematizados y estadísticamente refrendados. La propuesta del tesista propone enriquecer el actual homo economicus, incorporando la importancia de las relaciones con el grupo (coactivas, coercitivas o motivacionales), a través de un nuevo objeto de estudio: los Proyectos. Es mediante los Proyectos, donde los individuos y los grupos en los que interactúan, transan y organizan sus esfuerzos. El problema reside en que, no existe hasta la fecha, una sistematización y modelización de los Proyectos como objeto de estudio en las Ciencias Sociales. Sin embargo, hay una amplia experiencia de análisis y sistematización de Proyectos tanto en la Economía de la Empresa (Management, Business Administration), como en la Economía Pública. En esta Tesis se estudia todo lo publicado recientemente sobre los Proyectos de Inversión Pública (PIPs) y su eficiencia en Latinoamérica. En la Segunda Parte, centrada en un Trabajo Empírico y su modelización, el tesista crea una Base de Datos (BdD) primaria, a partir del Banco de Proyectos (BdP) del Ministerio de Economía y Finanzas (MEF) del Perú (2001-2014), que recoge todos los Proyectos de Inversión Pública (PIP), cerca de 400.000 PIPs Iniciales, los tabula en 48 categorías y posteriormente, “deja hablar a los datos” jugando a relacionar, correlacionar, inducir hipótesis y verificarlas mediante un sistema que se centra en la operativa tipo “Big Data”. A esto le denomina “triangular” porque mezcla en el esfuerzo, herramientas de Estadística Descriptiva, Estadística Inferencial y Econometría para poder refrendar el conocimiento inducido, que siempre en ciencia, es una mera certeza probabilística. El tesista concluye que en el caso del Sistema Nacional de Inversión Pública del Perú (SNIP) y más específicamente, de los procesos administrativos que emplea -denominados “Ciclo PIP”-, queda claro que se está trabajando con “fenómenos emergentes” cuyo comportamiento no se adapta a una Distribución Normal. Y que dicho comportamiento errático se debe a que la Inversión Pública es cíclica (Ecuación Evolutiva de Price) y a que el “Ciclo PIP” opera a todo nivel (GN, GR, GL) en función de las relaciones entre los miembros que componen su red. Ergo, es un tema a Analizar con Social Network Analysis (Análisis Social de Redes, ARS). El tesista concluye que las redes de “Ciclo PIP” en el Perú fallan principalmente por problemas de escasez de personal técnico multisectorial debidamente cualificado. A manera de conclusión, propone la creación de una Plataforma Web 3.0 (metadatos), que utilice un Sistema de Razonamiento Basado en Casos (SRBC) para aprovechar el conocimiento que dimana de los éxitos y fracasos de los propios PIPs, con el fin de facilitar las gestiones de los miembros de la red que formulan, evalúan y ejecutan los PIPs en el Perú, tanto a nivel Municipal (GP) como Regional (GR) y Nacional (GN).

Estimating and forecasting generalized fractional Long memory stochastic volatility models

In recent years fractionally differenced processes have received a great deal of attention due to its flexibility in financial applications with long memory. This paper considers a class of models generated by Gegenbauer polynomials, incorporating the long memory in stochastic volatility (SV) components in order to develop the General Long Memory SV (GLMSV) model. We examine the statistical properties of the new model, suggest using the spectral likelihood estimation for long memory processes, and investigate the finite sample properties via Monte Carlo experiments. We apply the model to three exchange rate return series. Overall, the results of the out-of-sample forecasts show the adequacy of the new GLMSV model.

Volatility spillovers in EMU sovereign bond markets

We analyse volatility spillovers in EMU sovereign bond markets. First, we examine the unconditional patterns during the full sample (April 1999-January 2014) using a measure recently proposed by Diebold and Yılmaz (2012). Second, we make use of a dynamic analysis to evaluate net directional volatility spillovers for each of the eleven countries under study, and to determine whether core and peripheral markets present differences. Finally, we apply a panel analysis to empirically investigate the determinants of net directional spillovers of this kind.

Extended theory about the allocation of time: Description and application to the increase in the retirement age policies

This paper revises mainstream economic models which include time use in an explicit and endogenous manner, suggesting a extended theory which escape from the main problem existing in the literature. In order to do it, we start by presenting in section 2 the mainstream time use models in economics, showing their main features. Once this is done, we introduce the reader in the main problems this kind of well established models imply, within section 3, being the most highlighted the problem of joint production. Subsequently, we propose an extended theory which solves the problem of joint production; this is extensively described in section 4. Last, but not least, we apply this model to offer a time use analysis of the effect of a policy which increases the retirement age in a life-cycle perspective for a representative individual.

Modelling and testing volatility spillovers in oil and financial markets for USA, UK and China

The primary purpose of the paper is to analyze the conditional correlations, conditional covariances, and co-volatility spillovers between international crude oil and associated financial markets. The paper investigates co-volatility spillovers (namely, the delayed effect of a returns shock in one physical or financial asset on the subsequent volatility or co-volatility in another physical or financial asset) between the oil and financial markets. The oil industry has four major regions, namely North Sea, USA, Middle East, and South-East Asia. Associated with these regions are two major financial centers, namely UK and USA. For these reasons, the data to be used are the returns on alternative crude oil markets, returns on crude oil derivatives, specifically futures, and stock index returns in UK and USA. The paper will also analyze the Chinese financial markets, where the data are more recent. The empirical analysis will be based on the diagonal BEKK model, from which the conditional covariances will be used for testing co-volatility spillovers, and policy recommendations. Based on these results, dynamic hedging strategies will be suggested to analyze market fluctuations in crude oil prices and associated financial markets.

Testing co-volatility spillovers for natural gas spot, futures and ETF spot using dynamic conditional covariances

There is substantial empirical evidence that energy and financial markets are closely connected. As one of the most widely-used energy resources worldwide, natural gas has a large daily trading volume. In order to hedge the risk of natural gas spot markets, a large number of hedging strategies can be used, especially with the rapid development of natural gas derivatives markets. These hedging instruments include natural gas futures and options, as well as Exchange Traded Fund (ETF) prices that are related to natural gas stock prices. The volatility spillover effect is the delayed effect of a returns shock in one physical, biological or financial asset on the subsequent volatility or co-volatility of another physical, biological or financial asset. Investigating volatility spillovers within and across energy and financial markets is a crucial aspect of constructing optimal dynamic hedging strategies. The paper tests and calculates spillover effects among natural gas spot, futures and ETF markets using the multivariate conditional volatility diagonal BEKK model. The data used include natural gas spot and futures returns data from two major international natural gas derivatives markets, namely NYMEX (USA) and ICE (UK), as well as ETF data of natural gas companies from the stock markets in the USA and UK. The empirical results show that there are significant spillover effects in natural gas spot, futures and ETF markets for both USA and UK. Such a result suggests that both natural gas futures and ETF products within and beyond the country might be considered when constructing optimal dynamic hedging strategies for natural gas spot prices.

Volatility spillovers for spot, futures, and ETF prices in energy and agriculture

The agricultural and energy industries are closely related, both biologically and financially. The paper discusses the relationship and the interactions on price and volatility, with special focus on the covolatility spillover effects for these two industries. The interaction and covolatility spillovers or the delayed effect of a returns shock in one asset on the subsequent volatility or covolatility in another asset, between the energy and agricultural industries is the primary emphasis of the paper. Although there has already been significant research on biofuel and biofuel-related crops, much of the previous research has sought to find a relationship among commodity prices. Only a few published papers have been concerned with volatility spillovers. However, it must be emphasized that there have been numerous technical errors in the theoretical and empirical research, which needs to be corrected. The paper not only considers futures prices as a widely-used hedging instrument, but also takes an interesting new hedging instrument, ETF, into account. ETF is regarded as index futures when investors manage their portfolios, so it is possible to calculate an optimal dynamic hedging ratio. This is a very useful and interesting application for the estimation and testing of volatility spillovers. In the empirical analysis, multivariate conditional volatility diagonal BEKK models are estimated for comparing patterns of covolatility spillovers. The paper provides a new way of analyzing and describing the patterns of covolatility spillovers, which should be useful for the future empirical analysis of estimating and testing covolatility spillover effects.

An econometric analysis of ETF and ETF futures in financial and energy markets using generated regressors

It is well known that that there is an intrinsic link between the financial and energy sectors, which can be analyzed through their spillover effects, which are measures of how the shocks to returns in different assets affect each other’s subsequent volatility in both spot and futures markets. Financial derivatives, which are not only highly representative of the underlying indices but can also be traded on both the spot and futures markets, include Exchange Traded Funds (ETFs), which is a tradable spot index whose aim is to replicate the return of an underlying benchmark index. When ETF futures are not available to examine spillover effects, “generated regressors” may be used to construct both Financial ETF futures and Energy ETF futures. The purpose of the paper is to investigate the covolatility spillovers within and across the US energy and financial sectors in both spot and futures markets, by using “generated regressors” and a multivariate conditional volatility model, namely Diagonal BEKK. The daily data used are from 1998/12/23 to 2016/4/22. The data set is analyzed in its entirety, and also subdivided into three subset time periods. The empirical results show there is a significant relationship between the Financial ETF and Energy ETF in the spot and futures markets. Therefore, financial and energy ETFs are suitable for constructing a financial portfolio from an optimal risk management perspective, and also for dynamic hedging purposes.

Asymptotic Theory for Extended Asymmetric Multivariate GARCH Processes

The paper considers various extended asymmetric multivariate conditional volatility models, and derives appropriate regularity conditions and associated asymptotic theory. This enables checking of internal consistency and allows valid statistical inferences to be drawn based on empirical estimation. For this purpose, we use an underlying vector random coefficient autoregressive process, for which we show the equivalent representation for the asymmetric multivariate conditional volatility model, to derive asymptotic theory for the quasi-maximum likelihood estimator. As an extension, we develop a new multivariate asymmetric long memory volatility model, and discuss the associated asymptotic properties.

Realized Matrix-Exponential Stochastic Volatility with Asymmetry, Long Memory and Spillovers

The paper develops a novel realized matrix-exponential stochastic volatility model of multivariate returns and realized covariances that incorporates asymmetry and long memory (hereafter the RMESV-ALM model). The matrix exponential transformation guarantees the positivedefiniteness of the dynamic covariance matrix. The contribution of the paper ties in with Robert Basmann’s seminal work in terms of the estimation of highly non-linear model specifications (“Causality tests and observationally equivalent representations of econometric models”, Journal of Econometrics, 1988, 39(1-2), 69–104), especially for developing tests for leverage and spillover effects in the covariance dynamics. Efficient importance sampling is used to maximize the likelihood function of RMESV-ALM, and the finite sample properties of the quasi-maximum likelihood estimator of the parameters are analysed. Using high frequency data for three US financial assets, the new model is estimated and evaluated. The forecasting performance of the new model is compared with a novel dynamic realized matrix-exponential conditional covariance model. The volatility and co-volatility spillovers are examined via the news impact curves and the impulse response functions from returns to volatility and co-volatility.

La coevaluación y la evaluación por pares como herramienta de aprendizaje en el estudio de la Economía

Este proyecto propone una estrategia de evaluación encaminada a seguir avanzando en el diseño y aplicación de acciones innovadoras encaminadas a fomentar el aprendizaje activo del alumno comenzado en Fernández, Jiménez, Pérez, Robles y Ruiz (2015). En particular proponemos una nueva estrategia de evaluación formativa aplicada al estudio de la Economía que permita que el objetivo final del curso no sólo consista en lograr que los alumnos aprendan unos conocimientos específicos de la materia, sino que se mejore el desarrollo de competencias tanto propias de la disciplina como de carácter transversal en el proceso de aprendizaje. La acción propuesta consiste en la aplicación de un sistema de co-evaluación y evaluación por pares (CEEP) en un conjunto de asignaturas del área Economía de los grados de Economía y Banca, Finanzas y Seguros impartidos en la Facultad de Ciencias Económicas y Empresariales (FCEE) de la Universidad Complutense de Madrid. El proyecto abarca un número razonable de asignaturas correspondientes a distintas etapas de la formación del estudiante.

Volatility Spillover and Multivariate Volatility Impulse Response Analysis of GFC News Events

This paper applies two measures to assess spillovers across markets: the Diebold Yilmaz (2012) Spillover Index and the Hafner and Herwartz (2006) analysis of multivariate GARCH models using volatility impulse response analysis. We use two sets of data, daily realized volatility estimates taken from the Oxford Man RV library, running from the beginning of 2000 to October 2016, for the S&P500 and the FTSE, plus ten years of daily returns series for the New York Stock Exchange Index and the FTSE 100 index, from 3 January 2005 to 31 January 2015. Both data sets capture both the Global Financial Crisis (GFC) and the subsequent European Sovereign Debt Crisis (ESDC). The spillover index captures the transmission of volatility to and from markets, plus net spillovers. The key difference between the measures is that the spillover index captures an average of spillovers over a period, whilst volatility impulse responses (VIRF) have to be calibrated to conditional volatility estimated at a particular point in time. The VIRF provide information about the impact of independent shocks on volatility. In the latter analysis, we explore the impact of three different shocks, the onset of the GFC, which we date as 9 August 2007 (GFC1). It took a year for the financial crisis to come to a head, but it did so on 15 September 2008, (GFC2). The third shock is 9 May 2010. Our modelling includes leverage and asymmetric effects undertaken in the context of a multivariate GARCH model, which are then analysed using both BEKK and diagonal BEKK (DBEKK) models. A key result is that the impact of negative shocks is larger, in terms of the effects on variances and covariances, but shorter in duration, in this case a difference between three and six months.

US Antidumping Petitions and Revealed Comparative Advantage of Shrimp Exporting Countries

The paper explores the trade competitiveness of seven major shrimp exporting countries, namely Vietnam, China, Thailand, Ecuador, India, Indonesia and Mexico, to the USA. Specifically, we investigate whether the United States (US) antidumping petitions impact upon the bilateral revealed comparative advantage (RCA) indexes for each of the seven shrimp exporting countries with the USA. Monthly data from January 2003 to December 2014 and the panel data model are used to examine the determinants of the RCA for the shrimp exporting countries. The empirical results show the shrimp exporting countries have superior competitiveness against the shrimp market in the USA. Moreover, the RCA indexes are significantly negatively influenced by shrimp prices, and are positively affected by US income per capita. However, the EMS (Early Mortality Syndrome) shrimp disease, domestic US shrimp quantity, exchange rate, and US antidumping laws are found to have no significant impacts on the RCA indexes. In terms of policy implications, the USA should try to reduce production costs of shrimp in the US market instead of imposing antidumping petitions, and the shrimp exporting countries should maintain their comparative advantage and diversify into new markets.