We introduce a long memory autoregressive conditional Poisson (LMACP) model to model highly persistent time series of counts. The model is applied to forecast quoted bid-ask spreads, a key parameter in stock trading operations. It is shown that the LMACP nicely captures salient features of...

In this paper, we provide new empirical evidence on order submission activity and price impacts of limit orders at NASDAQ. Employing NASDAQ TotalView-ITCH data, we find that market participants dominantly submit limit orders with sizes equal to a round lot. Most limit orders are canceled almost...

The study concentrates on an analysis of the Czech stock market performed by an application of DCC MV GARCH model of Engle (2002). Data sample including years from 1994 to 2009 is represented by daily returns of Prague Stock Exchange index and other 11 major stock indices. There is found an...

This paper analyzes the empirical relationship between credit default swap, bond and stock markets during the period 2000-2002. Focusing on the intertemporal comovement, we examine weekly and daily lead-lag relationships in a vector autoregressive model and the adjustment between markets caused...

We measure the information content of monthly analyst consensus forecasts for one-year-forward earnings per share (EPS) based on two well-established price discovery measures drawn from the area of market micro-structure research. Employing a 36-year sample of large US companies listed in the...

Companies are cross-listed on multiple exchanges in different countries to take advantage of different market features. Due to difference in time zones, it is normally quite impossible to take advantage of instantaneous information spillover from market to market to generate abnormal return....

We examine the long-term relationship between signals derived from nine years of unstructured social media microblog text data and financial market developments in five major economic regions. Employing statistical language modeling techniques we construct directional sentiment metrics and link...