The aim of this paper is to introduce a two-step trading algorithm, named TI-SiSS. In the first step, using some technical analysis indicators and the two NLP-based metrics (namely Sentiment and Popularity) provided by FinScience and based on relevant news spread on social media, we construct a...

There has been an extraordinary decrease in order execution time on stock exchanges in the past two decades. A related question is whether there has been a similar reduction in orders of magnitude for the lengths of the lead lag time between stocks. If the answer is affirmative, and the lengths...

Recent European regulatory restrictions on dark trading induced an increase in sub-second frequent batch/periodic auctions (PA). We exploit this development to investigate the effects of PA on market quality. The restrictions are linked to an observable increase in PA and an economically...

We develop a theoretical framework and propose a relevant empirical analysis of the soybean complex prices cointegration relationship in a high-frequency setting. We allow for heterogeneous expectations among traders on the multi-asset price dynamics and characterize the resulting market...

As in many other sectors of EU economies, 'artificial intelligence' (AI) has entered the scene of the financial services industry as a game-changer. Trading on capital markets is undoubtedly one of the most promising AI application domains. A growing number of financial market players have in...

We examine the soundness of high-frequency trading (HFT) proxies that are widely defined on the limit order book (LOB) information. We use a unique TRTH (Thomson Reuters Tick History) millisecond time-stamped intraday trades and quotes dataset enriched with 10 levels of LOB depth messages for...

In present-day major financial markets around the world, adaptive automated trading systems are responsible for many more transactions than are human traders, and human traders have largely been replaced by trading machines that can process super-human quantities of data and react to market...

We study liquidity provision by competitive high-frequency trading firms (HFTs) in a dynamic trading model with private information. Liquidity providers face adverse selection risk from trading with privately informed investors and from trading with other HFTs that engage in latency arbitrage...