Published Papers

This paper illustrates the power of modern statistical modelling in estimating measures of market risk, here applied to the Brent and WTI spot price of oil. Both Value-at-Risk (VaR) and Expected Shortfall (ES) are cast in terms of conditional centiles based upon semiparametric regression models. Using the GAMLSS statistical framework, we stress the important aspects of selecting a highly flexible parametric distribution (skewed Student's t distribution) and of modelling both skewness and kurtosis as nonparametric functions of the price of oil futures. Furthermore, an empirical application characterises the relationship between spot oil prices and oil futures - exploiting the futures market to explain the dynamics of the physical market. Our results suggest that NYMEX WTI has heavier tails compared with the ICE Brent. Contrary to the common platitude of the industry, we argue that 'somebody knows something' in the oil business.

Introduction

1. This evidence is presented to the Select Committee to provide a perspective in terms of the threats, vulnerability and consequences of the UK Energy Supply System within a global-national context characterized by unprecedented uncertainties and increasingly complex intertwines. This contribution is based upon the ACEGES project (www.aceges.org). ACEGES stands for Agent-based Computational  Economics of the Global Energy  System. The ACEGES models the energy demand and supply of 216 countries.

2. The aim is not to present another set of quantifications for policymaking, as there are a number of reports and papers published in recent years. Rather the aim is to provide a coherent overview of i) the assumptions of the energy models used to produce the published quantifications and ii) the approach used to develop energy scenarios for the assessment of the UK's Energy Supply.

3. I am a specialist in the modelling of fuzzy phenomena and complex adaptive systems such as the Energy System. My research work aims to support evidence-based energy policy by means of controlled computational experiments. Currently, I am the Deputy Director of the Centre for International Business and Sustainability (CIBS) at the London Metropolitan Business School. I am also the organise of the "UK Energy Day: Sustainable Supply" which is part of the European network of events led by the Intelligent Energy Europe (IEE) agency of the European Commission (EC).

4. It is evident today that the long-term sustainability of the UK's energy system is under acute strain. Therefore the comments that follow mainly deal with the need to enhance:

a. The existing energy models to assess the sensitivity of the UK's energy supply.

b. The way of developing multidimensional global-national continuous scenarios for long-term assessment of the resilient of the UK energy system to international events.

I will start with the latter.

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This paper reproduces the performance of a geometric average Spot Energy Index by investing only in a subset of stocks from the Dow Jones Composite Average, the FTSE 100 and Bovespa Composite indexes, and in two pools including only stocks of the energy sector from the US and the UK respectively. Daily data are used and the index-tracking problem for passive investment is addressed with two innovative evolutionary algorithms; the differential evolution algorithm and the genetic algorithm, respectively. The performance of the suggested investment strategy is tested under three different scenarios: buy-and-hold, quarterly, and monthly rebalancing;accounting for transaction costs where necessary.