The European Carbon Market in Action: Lessons from the First Trading Period Interim Report

Abstract and PDF report are also available on the MIT Joint Program on the Science and Policy of Global Change website (http://globalchange.mit.edu/).The European Union Emissions Trading Scheme (EU ETS) is the largest greenhouse gas market ever established. The European Union is leading the world's first effort to mobilize market forces to tackle climate change. A precise analysis of the EU ETS's performance is essential to its success, as well as to that of future trading programs. The research program "The European Carbon Market in Action: Lessons from the First Trading Period," aims to provide such an analysis. It was launched at the end of 2006 by an international team led by Frank Convery, Christian De Perthuis and Denny Ellerman. This interim report presents the researchers' findings to date. It was prepared after the research program's second workshop, held in Washington DC in January 2008. The first workshop was held in Paris in April 2007. Two additional workshops will be held in Prague in June 2008 and in Paris in September 2008. The researchers' complete analysis will be published at the beginning of 2009.The research program “The European Carbon Market in Action: Lessons from the First Trading Period” has been made possible thanks to the support of: Doris Duke Charitable Foundation, BlueNext, EDF, Euronext, Orbeo, Suez, Total, Veolia

Improving the Impact of Market Reform on Agricultural Productivity in Africa: How Institutional Design Makes a Difference

Improving the Impact of Market Reform on Agricultural Productivity in Africa: How Institutional Design Makes a Difference Abstract: This paper reviews the emerging empirical record of agricultural marketing policy reform and agricultural productivity, drawing from research on food access and agricultural productivity supported by USAID’s Africa Bureau on seven countries in West, Eastern, and Southern Africa. We also examine key factors constraining past and future performance of the food systems in these countries. The paper concludes by identifying a set of policy issues for further consideration that would help provide the investment incentives to promote productivity growth for the millions of low-input semi-subsistence rural households in the region.food security, food policy, market reform, Agricultural and Food Policy, Marketing, Productivity Analysis, Downloads June 2008 - July 2009: 40, Q13,

Value-at-risk of carbon constraints : an input oriented approach of resource scarcity

The purpose of this study is to broaden the discussion on corporate enviromental risk exposure by integrating an oil scarcity factor. This broader approach can be utilized as a means of instigating a discussion on carbon risks beyond output oriented adaption and mitigation strategies. Even though the outcomes might not seem to be relevant for current economic activities, the recent discussion about oil prices affecting the global economy illustrates the future relevance of this topic; it is just a matter of time before risks related to future oil supply and endowment will emerge. --

The statistical properties of technical trading rules

A portfolio of 200 heterogeneous technical trading rules is tested for their directional predictabilities on the DJIAI from 1988 to 1999. We also explore several nonparametric techniques designed for brain research, and detected possibly other forms of dependencies more significant than the traditional linear autocorrelation for the time series. The overall conditional mean directional predictability is 46%. 36 percent of the rules have more than 50% directional predictability, and the top 20 percent rules has a 73% directional predictability, whereas the bottom 80 percent has a directional predictability of 40%. Buy signals consistently generate higher predictability than sell signals but do not commensurate with their respective risk levels. The relationship between two sub-periods is not stable, while the difference between the conditional mean directional predictability of buy only and sell only signals is highly significance. The belief that most successful rules have a directional predictability of 25% to 50% coincides with the mode of distribution. We observe counter intuitive relationship between volatility and directional predictability. The results of directional predictability in a downtrend concur with the argument that buy-and-hold strategy is not a suitable benchmark. Attempts are made to tackle the issues of small sample bias, data snooping, size of test window, bootstrap or t-test, and homogeneity. Issues are discussed on empirical testing for their real world applications, statistical and non-statistical interpretations; also randomness test; physical or biological science approach

Forecasting foreign exchange rates with adaptive neural networks using radial basis functions and particle swarm optimization

The motivation for this paper is to introduce a hybrid Neural Network architecture of Particle Swarm Optimization and Adaptive Radial Basis Function (ARBF-PSO), a time varying leverage trading strategy based on Glosten, Jagannathan and Runkle (GJR) volatility forecasts and a Neural Network fitness function for financial forecasting purposes. This is done by benchmarking the ARBF-PSO results with those of three different Neural Networks architectures, a Nearest Neighbors algorithm (k-NN), an autoregressive moving average model (ARMA), a moving average convergence/divergence model (MACD) plus a naïve strategy. More specifically, the trading and statistical performance of all models is investigated in a forecast simulation of the EUR/USD, EUR/GBP and EUR/JPY ECB exchange rate fixing time series over the period January 1999 to March 2011 using the last two years for out-of-sample testing

Financial Investment Analysis of Residential Rooftop Solar PV Systems in Norway : A Model-Based Approach to Analyse Profitability and the Effect of Key Variables Under Current Market Conditions

In light of increased electricity prices and high demand for renewable energy, solar PV deployment has risen rapidly and is expected to increase further, both globally and in Norway. Although a large part of the growth is related to utility-scale parks, rooftop systems on houses represent a significant potential for future deployment. Consequently, this thesis aims to build a general model for evaluating the profitability of residential rooftop solar PV systems in Norway. The profitability is not evaluated for specific projects but typical residential projects in Norway. The profitability question is evaluated using the net present value method. A cash flow model is developed for typical solar PV systems in six Norwegian cities. Initial investment costs are estimated from regressions on installation offers collected in the fall of 2022. Future electricity price scenarios are constructed using a combination of Nasdaq futures prices and long-term market analyses from NVE and Statnett. Sensitivity analyses are performed for variables like electricity price, initial investment cost, cost of capital, and share of generated electricity consumed internally. The thesis concludes that residential rooftop PV systems in Norway are not profitable unless electricity price scenarios well above historical prices are assumed. The geographic differences are strongly apparent, with the most profitable profiles located in Oslo, Kristiansand, and Bergen and the least profitable profiles located in Tromsø. The geographic differences are driven by meteorological conditions and differences in investment costs. Out of the variables that can be affected by the project owner, we found that the share of generated electricity consumed internally is the variable with the highest effect on profitability. We also argue that a reduction in investment cost is likely due to temporary high prices. This would have a strong positive impact on the profitability analysis.nhhma

On the profitability of technical trading

The sole use of price and related summary statistics in a technical trading strategy is an anathema to weak-form market efficiency. In practice, however, traders actively use technical analysis to make investment decisions which makes this an important, but often neglected, area for study. This thesis includes four empirical chapters, which provide important evidence on the profitability of technical trading. The results from the detailed analysis undertaken in this thesis have broad relevance to both academics and those in the investment community. Existing research has been predominantly confined to evaluating basic technical trading rules, such as moving averages. Crucially, this ignores chart patterns. Widely employed by practitioners, such patterns form a vital part of technical analysis. As the most important price pattern, the head and shoulders pattern is subjected to detailed and thorough examination in this thesis. A significant contribution is made by evaluating formations recognised and used by traders, in sharp contrast to limited existing studies. Furthermore, a new method is developed to establish how quickly profits from a head and shoulders strategy decay, which has important implications for traders. Existing research has identified both reversal and relative strength effects in financial asset returns. A key separator between these two findings is the formation and holding time over which portfolios of winners and losers are evaluated. Motivated by this, a very large sample of ultra high-frequency data is used to investigate intraday momentum and reversal effects. As well as being an important contribution to research in this field, the results are, once again, of relevance to practitioners. The need for further research into technical analysis is clearly demonstrated by point and figure charting. Whilst traders have made consistent use of the technique for around a century, the amount of existing research is extremely small. Point and figure has attractive data filtering properties, clear trading rules and is particularly suited to intraday technical analysis. Again, using a very large sample of high-frequency data, a detailed evaluation of the profitability of a point and figure trading strategy is undertaken