Modelling Time Series Count Data: An Autoregressive Conditional Poisson Model

This paper introduces and evaluates new models for time series count data. The Autoregressive Conditional Poisson model (ACP) makes it possible to deal with issues of discreteness, overdispersion (variance greater than the mean) and serial correlation. A fully parametric approach is taken and a marginal distribution for the counts is specified, where conditional on past observations the mean is autoregressive. This enables to attain improved inference on coefficients of exogenous regressors relative to static Poisson regression, which is the main concern of the existing literature, while modelling the serial correlation in a flexible way. A variety of models, based on the double Poisson distribution of Efron (1986) is introduced, which in a first step introduce an additional dispersion parameter and in a second step make this dispersion parameter time-varying. All models are estimated using maximum likelihood which makes the usual tests available. In this framework autocorrelation can be tested with a straightforward likelihood ratio test, whose simplicity is in sharp contrast with test procedures in the latent variable time series count model of Zeger (1988). The models are applied to the time series of monthly polio cases in the U.S between 1970 and 1983 as well as to the daily number of price change durations of :75$on the IBM stock. A .75$ price change duration is defined as the time it takes the stock price to move by at least .75$. The variable of interest is the daily number of such durations, which is a measure of intradaily volatility, since the more volatile the stock price is within a day, the larger the counts will be. The ACP models provide good density forecasts of this measure of volatility.Forecast; volatility; transactions data

Nonequilibrium dynamics in scalar hybrid models

We study by numerical simulations the transition from the metastable "false vacuum" to the broken symmetry phase in the preheating stage after cosmic inflation in a scalar hybrid model. We take quantum fluctuations and their back reaction into account by applying a one-loop bubble-resummation.Comment: 5 pages, 4 figures, contribution to the conference Strong and Electroweak Matter (SEWM2004), Helsinki, Finland, 16-19 June 200

Electricity, carbon and weather in France: where do we stand ?

As a tool to fight long run changes in climate the European Union explicitly introduced the emission trading scheme (EU ETS) on January 1, 2005, which aimed at reducing carbon emission by 8% by 2012, and was designed to operate in two phases. Using data related to the first phase, this article investigates the role that the EU ETS plays in the power generation market by taking into account the existence of possible cross-spillovers between the French carbon and the French electricity spot markets, the spot prices of natural gas and of oil, and climatic conditions in France and elsewhere. Results show that there is no short run relationship between the electricity and carbon returns, while there is a long run relationship. However, this relationship suffers from a disequilibrium in that the electricity price readjust in the long run. We also find that while there are own mean and own volatility spillovers in the two markets, there are no cross own mean and own volatility spillovers, indicating that the electricity spot market and the carbon spot market are not integrated. Finally, results underline the limited impact of weather on the interconnection of these markets.Carbon market, Electricity, Weather, Multivariate GARCH

Modeling International Financial Returns with a Multivariate Regime Switching Copula

In order to capture observed asymmetric dependence in international financial returns, we construct a multivariate regime-switching model of copulas. We model dependence with one Gaussian and one canonical vine copula regime. Canonical vines are constructed from bivariate conditional copulas and provide a very flexible way of characterizing dependence in multivariate settings. We apply the model to returns from the G5 and Latin American regions, and document two main findings. First, we discover that models with canonical vines generally dominate alternative dependence structures. Second, the choice of copula is important for risk management, because it modifies the Value at Risk (VaR) of international portfolio returns.Asymmetric dependence; Canonical vine copula; International returns; Regime-Switching; Risk Management; Value-at-Risk

Trading activity and liquidity supply in a pure limit order book market: An empirical analysis using a multivariate count data model.

In this paper we perform an empirical analysis of the trading process in a pure limit order book market, the Xetra system which operates at various European exchanges.We study how liquidity supply and demand as well as price volatility affect future trading activity and market resiliency, and discuss the results in the light of predictions implied by theoretical models of financial market microstructure. Parameter estimation and hypotheses testing is conducted using a new econometric methodology designed for the analysis of multivariate count processes.Market microstructure; Liquidity; Trading activity; Multivariate count process

Modelling international financial returns with a multivariate regime switching copula

In order to capture observed asymmetric dependence in international financial returns, we construct a multivariate regime-switching model of copula. We model dependence with one Gaussian and one canonical vine copula regime. Canonical vines are construted from bivariate conditional copulas and provide a very flexible way of characterizig dependence in multivariate settings. We apply the model to returns from the G5 and Latin American regions, and document two main findings. First, we discover that models with canonical vines generally dominate alternative dependence structures. Second, the choice of copula is important for risk management, because it modifies the Value at Risk (VaR) of international portfolio returns.asymmetric dependence, canonical vine copula, international returns, regime-switching, risk management, Value-at-Risk

Electricity, carbon and weather in France: where do we stand ?

As a tool to fight long run changes in climate the European Union explicitly introduced the emission trading scheme (EU ETS) on January 1, 2005, which aimed at reducing carbon emission by 8% by 2012, and was designed to operate in two phases. Using data related to the first phase, this article investigates the role that the EU ETS plays in the power generation market by taking into account the existence of possible cross-spillovers between the French carbon and the French electricity spot markets, the spot prices of natural gas and of oil, and climatic conditions in France and elsewhere. Results show that there is no short run relationship between the electricity and carbon returns, while there is a long run relationship. However, this relationship suffers from a disequilibrium in that the electricity price readjust in the long run. We also find that while there are own mean and own volatility spillovers in the two markets, there are no cross own mean and own volatility spillovers, indicating that the electricity spot market and the carbon spot market are not integrated. Finally, results underline the limited impact of weather on the interconnection of these markets

The price impact of extreme weather in developing countries

We examine the impact of extreme weather on consumer prices in developing countries by constructing a monthly data set of potential hurricane and flood destruction indices and linking these with consumer price data for 15 Caribbean islands. Our econometric model shows that the price impact of extreme weather events can be large. To illustrate potential welfare losses due to these price effects, we combine our estimates with price elasticities obtained from a demand system and with event probabilities for Jamaica. Our results show that while expected monthly losses are small, rare events can cause large falls in monthly welfare due to price increases

Competition, loan rates, and information dispersion in nonprofit and for-profit microcredit markets

We describe the competitive environment of microcredit markets globally and we study the effects of competition on loan rates of microfinance institutions (MFIs). We use a new database from rating agencies, covering 379 for-profit and nonprofit MFIs in 67 countries over 2002-2008. Controlling for interest rate ceilings and other countryspecific factors, we first find that nonprofits are relatively insensitive to industry-wide concentration changes, while for-profits charge significantly lower rates in less concentrated markets. Second, we find spillover effects between the for-profit and nonprofit segments. Third, we show that the effects of concentration are consistent with an information dispersion mechanism