This paper discusses the role of the credit rating agencies during the recent financial crises. In particular, it examines whether the agencies can add to the dynamics of emerging market crises. Academics and investors often argue that sovereign credit ratings are responsible for pronounced...

The use of GARCH models with stable Paretian innovations in financial modeling has been recently suggested in the literature. This class of processes is attractive because it allows for conditional skewness and leptokurtosis of financial returns without ruling out normality. This contribution...

Both unconditional mixed-normal distributions and GARCH models with fat-tailed conditional distributions have been employed for modeling financial return data. We consider a mixed-normal distribution coupled with a GARCH-type structure which allows for conditional variance in each of the...

The class of mixed normal conditional heteroskedastic (MixN-GARCH) models, which couples a mixed normal distributional structure with GARCH-type dynamics, has been shown to offer a plausible decomposition of the contributions to volatility, as well as excellent out-of-sample forecasting...

The paper documents the specification and estimation of an econometric model of the Brazilian stock market (Bovespa) using a GARCH(1,1) model. We used quarterly data for an estimation period spanning from January 1995 to December 2003. The empirical results show that GDP growth, exchange-rate...

The use of GARCH models with stable Paretian innovations in financial modeling has been recently suggested in the literature. This class of processes is attractive because it allows for conditional skewness and leptokurtosis of financial returns without ruling out normality. This contribution...

We present a simple model of a non-equilibrium self-organizing market where asset prices are partially driven by investment decisions of a bounded-rational agent. The agent acts in a stochastic market environment driven by various exogenous "alpha" signals, agent's own actions (via market...

The importance of solar energy has been growing in recent years. This raises the need for efficient modelling and forecasting methods. The existing methods are predominantly based on weather predictions or forecast solar radiation, which is not easy to convert into production forecast. Instead...

We propose a stochastic model for the maximal production of photovoltaic (PV) power on a daily basis based on data from three transmission system operators in Germany. We apply the sun intensity as a seasonal function and model the deseasonalized data by an autoregressive process with skewed...

We do comparison between maximal and daily average production of photovoltaic (PV) and wind energy based on a transmission operator in Germany by using statistical analysis with di erent seasonality function. We adopt sun intensity as a seasonal function for PV and trigonometric function for...