Statistical evidence of tax fraud on the carbon allowances market

The aim of this paper is to show evidence and to quantify with forensic econometric methods the impact of the Value Added Tax fraud on European carbon allowances markets. This fraud mainly occurred at the beginning of between the end of 2008 and the beginning of 2009. In this paper, we explore the financial mechanisms of the fraud and the impact on the market behavior as well as the reflexion on its econometric features. In a previous work, we showed that the European carbon market is strongly influenced by fundamentals factors as oil, energy, gas, coal and equity prices. Therefore, we calibrated Arbitrage Pricing Theory-like models and showed that they have a good forecast capacity. Those models enabled us to quantify the impact of each factor on the market. In this study, we focused more precisely on the benchmark contract for European carbon emissions prices over 2008 and 2009. We observed that during the first semester of 2009, there is a significant drop in our model performances and robustness and that the part of market volatility explained by fundamentals reduced. Therefore, we identified the period where the market was driven by VAT fraud movements and we were able to measure the value of this fraud. Soon after governments passed a law that cut the possibility of fraud occurrence the performance of the model improved rapidly. We estimate the impact of the VAT extortion on the carbon market at 1.3 billion euros.Carbon, EUA, energy, Arbitrage Pricing Theory, Switching regimes, hidden Markov Chain Model, forecast.

Dynamic factor analysis of carbon allowances prices: From classic Arbitrage Pricing Theory to Switching Regimes

The aim of this paper is to identify the fundamental factors that drive the allowances market and to built an APT-like model in order to provide accurate forecasts for CO2. We show that historic dependency patterns emphasis energy, natural gas, oil, coal and equity indexes as major factors driving the carbon allowances prices. There is strong evidence that model residuals are heavily tailed and asymmetric, thereby generalized hyperbolic distribution provides with the best fit results. Introducing dynamics inside the parameters of the APT model via a Hidden Markov Chain Model outperforms the results obtained with a static approach. Empirical results clearly indicate that this model could be used for price forecasting, that it is effective in and out of sample producing consisten results in allowances futures price prediction.Carbon, EUA, energy, Abritrage Pricing Theory, switching regimes, hidden Markov Chain Model, forecast.

Statistical evidence of tax fraud on the carbon allowances market

URL des Documents de travail : http://ces.univ-paris1.fr/cesdp/CESFramDP2010 Classification AMS : 47A15, 46A32, 47D20.Documents de travail du Centre d'Economie de la Sorbonne 2010.69 - ISSN : 1955-611XThe aim of this paper is to show evidence and to quantify with forensic econometric methods the impact of the Value Added Tax fraud on European carbon allowances markets. This fraud mainly occurred at the beginning of between the end of 2008 and the beginning of 2009. In this paper, we explore the financial mechanisms of the fraud and the impact on the market behavior as well as the reflexion on its econometric features. In a previous work, we showed that the European carbon market is strongly influenced by fundamentals factors as oil, energy, gas, coal and equity prices. Therefore, we calibrated Arbitrage Pricing Theory-like models and showed that they have a good forecast capacity. Those models enabled us to quantify the impact of each factor on the market. In this study, we focused more precisely on the benchmark contract for European carbon emissions prices over 2008 and 2009. We observed that during the first semester of 2009, there is a significant drop in our model performances and robustness and that the part of market volatility explained by fundamentals reduced. Therefore, we identified the period where the market was driven by VAT fraud movements and we were able to measure the value of this fraud. Soon after governments passed a law that cut the possibility of fraud occurrence the performance of the model improved rapidly. We estimate the impact of the VAT extortion on the carbon market at 1.3 billion euros.Le but de cet article est de quantifier la fraude à la TVA sur les allocations de carbone sur les marchés européens. Cette fraude a surtout été enregistrée entre 2008 et 2009. Dans cet article, nous explorons les mécanismes financiers de la fraude et l'impact sur le comportement du marché. Nous avons pu identifier la période où le marché a été alimentée par les mouvements de fraude à la TVA et mesurer la valeur de cette fraude. Après l'intervention des gouvernements pour uniformiser la réglementation de la TVA sur ces marchés, nous constatons que l'évolution des prix changent et leur prévision redevient possible

Dynamic factor analysis of carbon allowances prices: From classic Arbitrage Pricing Theory to Switching Regimes

URL des Documents de travail : http://ces.univ-paris1.fr/cesdp/cesdp2010.htmlDocuments de travail du Centre d'Economie de la Sorbonne 2010.62 - ISSN : 1955-611XThe aim of this paper is to identify the fundamental factors that drive the allowances market and to built an APT-like model in order to provide accurate forecasts for CO2. We show that historic dependency patterns emphasis energy, natural gas, oil, coal and equity indexes as major factors driving the carbon allowances prices. There is strong evidence that model residuals are heavily tailed and asymmetric, thereby generalized hyperbolic distribution provides with the best fit results. Introducing dynamics inside the parameters of the APT model via a Hidden Markov Chain Model outperforms the results obtained with a static approach. Empirical results clearly indicate that this model could be used for price forecasting, that it is effective in and out of sample producing consisten results in allowances futures price prediction.Le but de cet article est d'identifier les facteurs fondamentaux qui influencent le marché du CO2 et de construire un modèle APT à partir de ces fondamentaux. Nous montrons l'importance du gaz naturel, du pétrole, du charbon et des indices boursier. Il est manifeste que les résidus du modèle sont asymétriques et sont correctement modélisés à partir d'une distribution généralisée hyperbolique. Le modèle APT est étendu par l'introduction de paramètres évoluant à l'aide d'une chaine de Markov. Les résultats empiriques indiquent clairement que ce modèle pourrait être utilisé pour la prévision des prix, qu'il est efficace dans et hors de l'échantillon et produit des résultats cohérents pour les allocations de prévision des prix à terme

Forecasting Strategies for Carbon Allowances Prices: From Classic Arbitrage Pricing Theory to Switching Regimes

International audienc

Dynamic factor analysis of carbon allowances prices: From classic Arbitrage pricing Theory to Switching Regimes

International audienceThe aim of this paper is to identify the fundamental factors that drive the allowances market and to built an APT-like model in order to provide accurate forecasts for CO2. We show that historic dependency patterns emphasis energy, natural gas, oil, coal and equity indexes as major factors driving the carbon allowances prices. There is strong evidence that model residuals are heavily tailed and asymmetric, thereby generalized hyperbolic distribution provides with the best fit results. Introducing dynamics inside the parameters of the APT model via a Hidden Markov Chain Model outperforms the results obtained with a static approach. Empirical results clearly indicate that this model could be used for price forecasting, that it is effective in and out of sample producing consisten results in allowances futures price prediction

Statistical evidence of tax fraud on the carbon allowances market.

The aim of this paper is to show evidence and to quantify with forensic econometric methods the impact of the Value Added Tax fraud on European carbon allowances markets. This fraud mainly occurred at the beginning of between the end of 2008 and the beginning of 2009. In this paper, we explore the financial mechanisms of the fraud and the impact on the market behavior as well as the reflexion on its econometric features. In a previous work, we showed that the European carbon market is strongly influenced by fundamentals factors as oil, energy, gas, coal and equity prices. Therefore, we calibrated Arbitrage Pricing Theory-like models and showed that they have a good forecast capacity. Those models enabled us to quantify the impact of each factor on the market. In this study, we focused more precisely on the benchmark contract for European carbon emissions prices over 2008 and 2009. We observed that during the first semester of 2009, there is a significant drop in our model performances and robustness and that the part of market volatility explained by fundamentals reduced. Therefore, we identified the period where the market was driven by VAT fraud movements and we were able to measure the value of this fraud. Soon after governments passed a law that cut the possibility of fraud occurrence the performance of the model improved rapidly. We estimate the impact of the VAT extortion on the carbon market at 1.3 billion euros.Carbon, EUA, energy, arbitrage pricing theory, switching regimes, hidden Markov Chain Model, forecast.

Dynamic factor analysis of carbon allowances prices : From classic Arbitrage Pricing Theory to Switching Regimes.

The aim of this paper is to identify the fundamental factors that drive the allowances market and to built an APT-like model in order to provide accurate forecasts for CO2. We show that historic dependency patterns emphasis energy, natural gas, oil, coal and equity indexes as major factors driving the carbon allowances prices. There is strong evidence that model residuals are heavily tailed and asymmetric, thereby generalized hyperbolic distribution provides with the best fit results. Introducing dynamics inside the parameters of the APT model via a Hidden Markov Chain Model outperforms the results obtained with a static approach. Empirical results clearly indicate that this model could be used for price forecasting, that it is effective in and out of sample producing consisten results in allowances futures price prediction.Carbon, EUA, energy, Arbitrage Pricing Theory, switching regimes, hidden Markov Chain model, forecast.