In this study we evaluate the effectiveness of augmenting numerical market data with textual-
news data, using data mining methods, for forecasting stock returns in intraday trading …

Innovative automated execution strategies like Algorithmic Trading gain significant market
share on electronic market venues worldwide, although their impact on market outcome has …

Being equipped with a unique high-frequency dataset that enables us to precisely identify
algorithmic trading (ie computergenerated) activity, we provide strong evidence that …

Financial markets are characterised by high levels of complexity and non-linearity.
Information systems have often been applied to support investors by forecasting price …

This paper examines the use, determinants, and impact of anonymous orders in a market
where disclosure of broker identity in the trading screen is voluntary. We find that most …

After exchanges and alternative trading venues have introduced electronic execution
mechanisms worldwide, the focus of the securities trading industry shifted to the use of fully …

This paper presents a continuous-time model of intraday trading, pricing, and liquidity with
dynamic TWAP and VWAP benchmarks. The model is solved in closed-form for the …

This paper presents a continuous-time equilibrium model of TWAP trading and liquidity
provision in a market with multiple strategic investors with intraday trading targets. We …

In the course of technological evolution security markets offer low-latency access to their
customers. Although latency figures are used as marketing instruments, only little research …

In this paper, we develop an extended dynamic programming (DP) approach to solve the
problem of minimising execution cost in block trading of securities. To make the problem …