The interaction between stock price process and market news has been widely analyzed by investors on different markets. Previous works, however, focus either on market news purely as exogenous factors that tend to lead price process or on the analysis of how past stock price process can affect future stock returns. To take a step forward, we quantitatively integrate information from both market...

We establish several new stylised facts concerning the intra-day seasonalities of stock dynamics. Beyond the well known U-shaped pattern of the volatility, we find that the average correlation between stocks increases throughout the day, leading to a smaller relative dispersion between stocks. Somewhat paradoxically, the kurtosis (a measure of volatility surprises) reaches a minimum at the open...

In this paper a novel algorithm to determine the minimum cost reserves for power systems with high wind penetration, is presented. We first determine the status and schedule of each generating unit by solving a deterministic unit commitment problem, where only the wind power forecast is taken into account. Having then computed the generation schedule, we formulate a linear stochastic program wi...

Due to uncertain nature of wind and photovoltaic power units, the participation of this units in electricity markets is subjected to significant deviation penalties. This issue leads to despondency or even admission of these units in the competitive environment. With regard to this fact that the low deviations are available when predictions are performed in a short-term horizon and also distrib...

A fractal approach is used to analyze financial time series, applying different degrees of time resolution, and the results are interrelated. Some fractal properties of foreign exchange (FX) data are found. In particular, the mean size of the absolute values of price changes follows a “fractal” scaling law (a power law) as a function of the analysis time interval ranging from a few minutes up t...

This paper proposes a structural time series model for the intra-day price dynamics on fragmented financial markets. We generalize the structural model of Hasbrouck (1993) to a multi-variate setting. We discuss identification issues and propose a new measure for the contribution of each market to price discovery. We illustrate the model by an empirical example using Nasdaq dealer quotes.

This article presents XGB-Chiarella, a powerful new approach for deploying agent-based models to generate realistic intra-day artificial financial price data.

Ensuring the security of stable, efficient and reliable energy supplies has intensified interconnections between markets. Imbalances supply demand due to operational failures, congestion other sources risk faced by market connections can lead a system that is vulnerable spread its spill-over. The main contribution this paper development estimation Bayesian Graphical Vector-AutoRegression Struct...