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.

Measuring the impact of international R&D cooperation: the case of Spanish firms participating in the EU Framework Programme

The objective of this paper is to analyse the effects of international R&D cooperation on firms’ economic performance. Our approach, based on a complete data set with information about Spanish participants in research joint ventures supported by the EU Framework Programme during the period 1995-2005, establishes a recursive model structure to capture the relationship between R&D cooperation, knowledge generation and economic results, which are measured by labour productivity. In the analysis we take into account that the participation in this specific type of cooperative projects implies a selection process that includes both the self-selection by participants to join the consortia and the selection of projects by the European Commission to award the public aid. Empirical analysis has confirmed that: (1) R&D co-operation has a positive impact on the technological capacity of firms, captured through intan-gible fixed assets and (2) the technological capacity of firms is positively related to their productivity.