On the impact of transport model errors for the estimation of CO2 surface fluxes from GOSAT observations

A series of observing system simulation experiments is presented in which column averaged dry air mole fractions of CO2 (XCO2) from the Greenhouse gases Observing SATellite (GOSAT) are made consistent or not with the transport model embedded in a flux inversion system. The GOSAT observations improve the random errors of the surface carbon budget despite the inconsistency. However, we find biases in the inferred surface CO2 budget of a few hundred MtC/a at the subcontinental scale, that are caused by differences of only a few tenths of a ppm between the simulations of the individual XCO2 soundings. The accuracy and precision of the inverted fluxes are little sensitive to an 8-fold reduction in the data density. This issue is critical for any future satellite constellation to monitor XCO2 and should be pragmatically addressed by explicitly accounting for transport errors in flux inversion systems

Stimulus sensitivity of a spiking neural network model

Some recent papers relate the criticality of complex systems to their maximal capacity of information processing. In the present paper, we consider high dimensional point processes, known as age-dependent Hawkes processes, which have been used to model spiking neural networks. Using mean-field approximation, the response of the network to a stimulus is computed and we provide a notion of stimulus sensitivity. It appears that the maximal sensitivity is achieved in the sub-critical regime, yet almost critical for a range of biologically relevant parameters

Fluctuations for mean-field interacting age-dependent Hawkes processes

The propagation of chaos and associated law of large numbers for mean-field interacting age-dependent Hawkes processes (when the number of processes n goes to +$\infty$) being granted by the study performed in (Chevallier, 2015), the aim of the present paper is to prove the resulting functional central limit theorem. It involves the study of a measure-valued process describing the fluctuations (at scale n --1/2) of the empirical measure of the ages around its limit value. This fluctuation process is proved to converge towards a limit process characterized by a limit system of stochastic differential equations driven by a Gaussian noise instead of Poisson (which occurs for the law of large numbers limit)

EUAs and CERs : Interactions in a Markov regime-switching environment.

This paper analyzes jointly the time series of European Union Allowances (EUAs) and Certified Emissions Reductions (CERs) in a Markov regime-switching environment. The purpose consists in capturing the interactions between the two time series - which have been highlighted in previous literature - with respect to the underlying business cycle. Given the recent period of economic growth and financial crisis, regime switching models appear indeed interesting to shed new light on the data. The main result of the paper features a switch from a low-growth period to a high-growth period in July 2009, in a context of timid economic recovery. Besides, the Markov regime-switching model reveals that significant interactions exist between EUAs (during expansions and recessions) and CERs (mostly during expansions). Colletively, these results could be of use to regulatory authorities, academics and financial agents (investment bankers, analysts, asset managers).EUA; CER; Markov regime-switching;

Carbon Prices during the EU ETS Phase II: Dynamics and Volume Analysis

The European Union Emissions Trading Scheme (EU ETS) is the largest emissions trading scheme to date. This article summarizes the principle elements behind the trading system, and details the carbon price dynamics during Phase II (2008-2012), along with an analysis of traded volumes. The main findings emphasize that the EU ETS is a rapidly growing market, which yields to innovative learning process for all participants involved: policy makers, industrial operators, and financial analysts. Besides, these results shed some light on the usefulness of credit project mechanisms, which may result in the medium-term in integrated ‘world' carbon markets between various regional and/or national ETS.EU ETS; Carbon Price; Phase II; CER ; Spot Price ; Futures Price ; Options Price

A Note on Cointegrating and Vector Autoregressive Relationships between CO2 allowances spot and futures prices

This article investigates the cointegrating and vector autoregressive relationships in CO2 allowances spot and futures prices, valid for compliance under the EU Emissions Trading Scheme (EU ETS). Our empirical analysis yields to reject a cointegrating relationship between CO2 spot and futures prices, when accounting for the presence of a structural break in February 2009 (possibly due to the delayed impact of the ``credit crunch'' crisis). Then, a vector autoregression analysis (complemented by impulse response functions) indicates that futures prices are relevant for price formation in the spot market (while the opposite is not true). Overall, this analysis appears useful to making informed hedging decisions in the banking and finance industries, while allowing regulated utilities to relate futures prices to better forecasts of spot prices.CO2 Price; Cointegration; VAR

EUAs and CERs: Vector Autoregression, Impulse Response Function and Cointegration Analysis

EUAs are European Union Allowances traded on the EU Emissions Trading Scheme (EU ETS), while Certified Emissions Reductions (CERs) arise from the Clean Development Mechanism under the Kyoto Protocol. These emissions assets attract an increasing attention among brokers, investors and operators on emissions markets, because they may be both used for compliance under the EU ETS (up to fixed limits). This paper proposes a statistical analysis of the inter-relationships between EUA and CER price series, by using vector autoregression, impulse response function, and cointegration analysis on daily data from March 9, 2007 to January 14, 2010. The central results show that EUAs and CERs affect each other significantly through the vector autoregression model, and react quite rapidly to shocks on each other through the impulse response function analysis. Most importantly, both price series are found to be cointegrated, with EUAs leading the price discovery process in the long-term through the vector error correction mechanism.EUA, CER, Vector Autoregression, Impulse Response Function, Cointegration, Vector Error Correction Model, EU ETS, Price Discovery.