Using extreme value theory to measure value-at-risk for daily electricity spot prices

The recent deregulation in electricity markets worldwide has heightened the importance of risk management in energy markets. Assessing Value-at-Risk (VaR) in electricity markets is arguably more difficult than in traditional financial markets because the distinctive features of the former result in a highly unusual distribution of returns-electricity returns are highly volatile, display seasonalities in both their mean and volatility, exhibit leverage effects and clustering in volatility, and feature extreme levels of skewness and kurtosis. With electricity applications in mind, this paper proposes a model that accommodates autoregression and weekly seasonals in both the conditional mean and conditional volatility of returns, as well as leverage effects via an EGARCH specification. In addition, extreme value theory (EVT) is adopted to explicitly model the tails of the return distribution. Compared to a number of other parametric models and simple historical simulation based approaches, the proposed EVT-based model performs well in forecasting out-of-sample VaR. In addition, statistical tests show that the proposed model provides appropriate interval coverage in both unconditional and, more importantly, conditional contexts. Overall, the results are encouraging in suggesting that the proposed EVT-based model is a useful technique in forecasting VaR in electricity markets. (c) 2005 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.

Contrasting models of land use regulation: Community, government and tourism development

This paper assesses the capacity of local communities and sub-national governments to influence patterns of tourism development, within the context of a globalizing economy. Through a comparison of the contrasting examples of Hawaii and Queensland, the paper indicates the consequences of different approaches to land use regulation. It points to the importance of planning and policy processes that integrate community interests, in order to achieve long-term, sustainable tourism development. Effective regulation of development can minimize the social and environmental impacts of tourism. The paper illustrates how community organizations and sub-national governments can articulate local interests, despite the global demands of investors for more deregulated markets in land.

Public investment and the risk premium for equity

Analysis of the equity premium puzzle has focused on private-sector capital markets. However, the existence of an anomalous equity premium raises important issues in the evaluation of public-sector investment projects. These issues are explored below. We begin by formalizing the argument that an equity premium may arise from uninsurable systematic risk in labour income, and show that, other things being equal, increases in public ownership of equity will improve welfare, up to the point where the equity premium is eliminated. Finally, we consider policy implications and the optimal extent of public ownership.

Noise trader risk and the welfare effects of privatization

Excessive volatility of asset prices like that generated in the 'noise trader' model of De Long et al. is one factor that plausibly might contribute to an explanation of the equity premium. We extend the De Long et al. model to allow for privatization of publicly-owned assets and assess the welfare effects of such privatization in the presence of excess volatility arising from noise traders' mistaken beliefs.

Asset Price Instability and Policy Responses: The Legacy of Liberalization

The problem of asset price bubbles, and more generally of instability in the financial system, has been a matter of concern since the 1980s but has only recently moved to the center of the macroeconomic policy debate. The main concern with bubbles arises when they burst, imposing losses on investors holding the bubble assets and potentially on the financial institutions that have extended credit to them. Asset price volatility is an inevitable consequence of financial market liberalization and, in extreme cases, generates asset price bubbles, the bursting of which can impose substantial economic and social costs. Policy responses within the existing liberalized financial system face daunting levels of uncertainty and risk. Given the pattern of increasing asset market volatility over recent decades and the policy issues highlighted in this paper, the future looks uncertain. Another significant cycle of asset price movements, especially in one of the major economies, could see a fundamental revision of thinking about the costs and benefits of liberalized financial systems.

What determines the finance-growth nexus? Empirical evidence for threshold models

This paper elaborates the notion of balanced'' financial development that is contingent on a country's general level of development. We develop an empirical framework to address this point, referring to threshold regressions and a bootstrap test for structural shift in a growth equation. We find that countries gain less from financial activity, if the latter fails to keep up with or exceeds what would follow from a balanced expansion path. These analyses contribute to the finance and growth literature in providing empirical support for the balanced'' financial development hypothesis.

The risk premium for equity: implications for resource allocation, welfare and policy

Analysis of the equity premium puzzle has focused on private sector capital markets. The object of this paper is to consider the welfare and policy implications of each of the broad classes of explanations of the equity premium puzzle. As would be expected, the greater the deviation from the first-best outcome implied by a given explanation of the equity premium puzzle, the more interventionist are the implied policy conclusions. Nevertheless, even explanations of the equity premium puzzle consistent with a general consumption-based asset pricing model have important welfare and policy implications.

A machine learning approach to intraday trading on foreign exchange markets

Foreign Exchange trading has emerged in recent times as a significant activity in many countries. As with most forms of trading, the activity is influenced by many random parameters so that the creation of a system that effectively emulates the trading process will be very helpful. In this paper we try to create such a system using Machine learning approach to emulate trader behaviour on the Foreign Exchange market and to find the most profitable trading strategy.

Incremental model transformation for the evolution of model-driven systems

Model transformations are an integral part of model-driven development. Incremental updates are a key execution scenario for transformations in model-based systems, and are especially important for the evolution of such systems. This paper presents a strategy for the incremental maintenance of declarative, rule-based transformation executions. The strategy involves recording dependencies of the transformation execution on information from source models and from the transformation definition. Changes to the source models or the transformation itself can then be directly mapped to their effects on transformation execution, allowing changes to target models to be computed efficiently. This particular approach has many benefits. It supports changes to both source models and transformation definitions, it can be applied to incomplete transformation executions, and a priori knowledge of volatility can be used to further increase the efficiency of change propagation.