Stock transaction data have become very detailed and enormous with the introduction of electronic-trading systems. This makes it a problem to store and to access,the data in later analyses such as mining useful gatterns and backtesting trading strategies. This paper investigates several storage methods in terms of both storage space and access efficiency and then proposes a new dynamic storage ...

The ease of Internet stock trading has lured relatively inexperienced investors into the financial markets. We study the consequences of the influx of these uninformed traders with a dynamic equilibrium framework. Our results show that these strategic uninformed online traders who adopt feedback strategies cannot outperform those who do not follow feedback strategies and that feedback trading c...

Modern financial markets compete aggressively for trading activity and investor interest. Information technology, once a crucial element in streamlining paper flows and operations, is now a strategic resource used in attracting or retaining market liquidity. Established exchanges introduce technology to enhance their markets. New market venues challenge the status quo and rely on technology to ...

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 sheds light on the means of those figures. This paper provides a performance measure on the effect of latency in the context of the competitive advantage of IT. Based on a historical dataset of Deutsche Börse’s el...

The algorithmic stock trading has developed exponentially in the past years, while the automatism of the technical analysis was the main research are for implementing the algorithms. This paper proposes a model for a trading algorithm that combines the signals from different technical indicators in order to provide more accurate trading signals.

The presumed source of the volatility is a trading strategy called “programmed trading.”2 This strategy, which essentially involves trading on small and shortlived price differences for the same group of stocks in the spot, futures and options markets, is not new. The introduction of stock jnde~futures around 1982 and the application of computer techniques to monitor price differences and trigg...

A great deal of work has been published over the past decade on the application of neural networks to stockmarket trading. Individual researchers have developed their own techniques for designing and testing these neural networks, and this presents a difficulty when trying to learn lessons and compare results. This paper aims to present a methodology for designing robust mechanical trading syst...

The emergence of IT-based trading activities like algorithmic trading or high-frequency trading alters the traditional trading environment within financial markets. Thus, the question arises whether this technological arms race positively affects market quality or represents a risk related to market integrity. Within this study, we evaluate the order-to-trade-ratio for measuring overall ITbased...