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.

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.

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.

El papel de los carteles de la División de Gráfica y Cine de Parques y Recreo Público en la redefinición colonial del Puerto Rico de mediados del siglo XX

El cartel serigráfico del proyecto de carteles del Taller de Cinema y Gráfica de Parques y Recreo Público se utilizó como medio para educar e insertar a las grandes masas dentro de las reformas coloniales ocurridas como consecuencia de la entrada de Estados Unidos a la Segunda Guerra Mundial y readiestrar a la población puertorriqueña, entonces compuesta por campesinos, para servir como mano de obra barata y dócil al proyecto colonial y a los beneficiarios del proyecto de industrialización de la posguerra. Se ha dicho en innumerables ocasiones que el camino al infierno está repleto de buenas intenciones; este es el relato de un viaje de ida. Los carteles de la División de Cinema y Gráfica de Parques y Recreo Público mantienen desde el origen varios elementos inquietantes de lo que se podría denominar como la política de reconstrucción de una colonia, de un territorio objeto de la sujeción/subyugación por parte de otro país, y presentarlo como un objetivo plausible, de consideración y cumplimiento con los derechos humanos fundamentales...

A Livestock-Associated, Multidrug-Resistant, Methicillin-Resistant Staphylococcus aureus Clonal Complex 97 Lineage Spreading in Dairy Cattle and Pigs in Italy

Pandemic methicillin-resistant Staphylococcus aureus (MRSA) clonal complex 97 (CC97) lineages originated from livestock-to-human host jumps. In recent years, CC97 has become one of the major MRSA lineages detected in Italian farmed animals. The aim of this study was to characterize and analyze differences in MRSA and methicillin-susceptible S. aureus (MSSA) mainly of swine and bovine origins. Forty-seven CC97 isolates, 35 MRSA isolates, and 6 MSSA isolates from different Italian pig and cattle holdings; 5 pig MRSA isolates from Germany; and 1 human MSSA isolate from Spain were characterized by macrorestriction pulsed-field gel electrophoresis (PFGE) analysis, multilocus sequence typing (MLST), spa typing, staphylococcal cassette chromosome mec (SCCmec) typing, and antimicrobial resistance pattern analysis. Virulence and resistance genes were investigated by PCR and microarray analysis. Most of the isolates were of SCCmec type V (SCCmec V), except for two German MRSA isolates (SCCmec III). Five main clusters were identified by PFGE, with the German isolates (clusters I and II) showing 60.5% similarity with the Italian isolates, most of which (68.1%) grouped into cluster V. All CC97 isolates were Panton-Valentine leukocidin (PVL) negative, and a few (n = 7) tested positive for sak or scn. All MRSA isolates were multidrug resistant (MDR), and the main features were erm(B)- or erm(C)-mediated (n = 18) macrolide-lincosamide-streptogramin B resistance, vga(A)-mediated (n = 37) pleuromutilin resistance, fluoroquinolone resistance (n = 33), tet(K) in 32/37 tet(M)-positive isolates, and blaZ in almost all MRSA isolates. Few host-associated differences were detected among CC97 MRSA isolates: their extensive MDR nature in both pigs and dairy cattle may be a consequence of a spillback from pigs of a MRSA lineage that originated in cattle as MSSA and needs further investigation. Measures should be implemented at the farm level to prevent spillover to humans in intensive farming areas.