Technological innovations currently alter the traditional value chain in securities trading. Investment companies that used to buy trading services from their brokers are now enabled by technology to emulate core competencies of their brokers themselves. To investigate the adoption decision regarding one of those new technologies – Algorithmic Trading – a survey among the top European buy-side ...

In investigating the effects of algorithmic trading on stock market liquidity and commonality in liquidity in different market conditions in an electronic limit order market, we find algorithmic trading increases stock liquidity by narrowing quoted and effective bid–ask spreads. Furthermore, algorithmic trading decreases commonality in liquidity; this finding is robust across a variety of liqui...

Most stock markets are characterized by a number of parallel operating trading systems which interact intensively with each other. Usually, smaller trading platforms take the leading domestic main market as a benchmark in the price discovery process and for closing open trading positions. But what happens if the smaller trading systems suddenly have to act without this benchmark platform? We ex...

This paper documents that speed is crucially important for high-frequency trading strategies based on U.S. macroeconomic news releases. Using order-level data on the highly liquid S&P 500 ETF traded on NASDAQ from January 6, 2009 to December 12, 2011, we find that a delay of 300 ms or more significantly reduces returns of news-based trading strategies. This reduction is greater for high impact ...

Information technology plays a major role to support the process of securities trading. Tactical trading decisions can be implemented more efficiently by gaining access to alternative trading systems, which provide access to additional liquidity and potentially better execution prices. This paper explores the business value provided by to so-called dark pools of liquidity, which can be accessed...

Technological innovations such as high frequency trading systems (HFT) and algorithmic trading systems have changed financial markets. We discuss technological and economic aspects of HFT and find that HFT have a major impact on all aspects of the internal market structure of exchanges. We use market quality measures on a unique dataset provided by NASDAQ in order to analyze the contribution of...

Computerized trading controlled by algorithms – “Algorithmic Trading” – has become a fashionable term in investment banking. We investigate a set of Xetra order data to find traces of algorithmic trading by studying the lifetimes of cancelled orders. Even though it is widely agreed that an algorithm must randomize its order activities to avoid exploitation by other traders, we still find system...

Does Algorithmic Trading Improve Liquidity? Algorithmic trading has sharply increased over the past decade. Equity market liquidity has improved as well. Are the two trends related? For a recent five-year panel of New York Stock Exchange (NYSE) stocks, we use a normalized measure of electronic message traffic as a proxy for algorithmic liquidity supply and trace the associations between liquidi...

92 AI MAGAZINE ■ The Trading Agent Competition (TAC) has now become an annual fixture since its inception in 2000. The competition was conceived with the objective of studying automated trading strategies by focusing the research community on the development of competing solutions to a common trading scenario. The success of past TAC events has motivated broadening the scope of the competition ...

In stock market, foreign currency exchange market, or any other asset trading system, there are high-density data, which is a typical data streams. And the trading rules are often the functions of many variables. The visualization of these systems is very important for users to do analysis and trading. So the problem is how to show the graph of the large data and multiple-variable functions. Th...