Online Exclusive Automated & Algorithmic Trading Articles

SUBSCRIBERS ONLYThe e-trading landscape is being radically transformed by two irresistible forces: proximity trading and cloud computing. Together they create rich opportunities for e-services providers. So what are the drivers and how can firms stay ahead of the curve?full story

FREE ARTICLELast week’s HIFREQ TRADE event in London provided some fascinating insights into high frequency trading and its effects on the market ‘fabric’. Bob Giffords, Independent Banking & Technology Analyst & Conference Chairman sums up some of the key points.full story

FREE ARTICLEAs trading fragments to multiple trading venues in a post-MiFID landscape, there has been considerable discussion about whether price formation can take place on the new trading venues (Multilateral Trading Facilities or MTFs) or whether it is inextricably linked to the “primary” or “listing” market.full story

SUBSCRIBERS ONLYKnight Capital’s Kee-Meng Tan draws on his experience from the US and predicts that it’s only a matter of time before traders are completely comfortable using alternative venues when the LSE is down.full story

SUBSCRIBERS ONLYTodd Golub, COO, Nasdaq OMX Europe offers his thoughts on the recent outages at the LSE and the way they were handled.full story

FREE ARTICLE… are paved with good technology. Working with key industry figures, Automated Trader has convened a round table on the enduring issue that is latency. Are there common practices emerging? One idea that has gained traction in the recent past is latency standardisation: would a latency standard help with measurement and benchmarking? And if so, how? That’s where we begin. Our round-table participants are gathered from across the industry.full story

FREE ARTICLEAs the competition to produce and quickly deploy profitable trading models continues to increase, many participants are starting to pay more attention to refining their model development process. In the third of three excerpts from their book "Quality MoneyManagement", Andrew Kumiega and Benjamin Van Vliet discuss the development of data cleaning algorithms. full story

FREE ARTICLEAs the competition to produce and quickly deploy profitable trading models continues to increase, many participants are starting to pay more attention to refining their model development process. In the first of three excerpts from their book "Quality Money Management", Andrew Kumiega and Benjamin Van Vliet provide an overview of an optimal process for trading model development. full story

FREE ARTICLEToday, Monte Carlo (MC) methods are widely used in finance to price derivative securities. In this approach, the value of the option is expressed in terms of an integral of very high dimensionality. Monte Carlo methods are used to estimate the value of this integral by brute force. These calculations consume a significant portion of the run-time and energy of financial data centers. Therefore, we present a hardware accelerator that computes the price of a European call option via MC. In our approach, after some initial setup, the entire MC simulation is performed by the FPGA. We demonstrate performance in excess of 250× that of a modern 3 GHz multi-core processor. By Nathan Woods, XtremeData, Inc.full story

FREE ARTICLEStatistical Arbitrage: Algorithmic Trading Insights and Techniques Chapter 2 Statistical Arbitragefull story

REGISTERED VIEWERSThe following excerpt is from Chapter 6 of David Aronson's recently published book "Evidence-Based Technical Analysis". Together with Chapters 4 and 5 of the book it addresses aspects of statistics that are particularly relevant to evidence-based (as opposed to subjective) technical analysis.full story

REGISTERED VIEWERSThe following excerpt is from Chapter 4 of David Aronson's recently published book "Evidence-Based Technical Analysis". Together with Chapters 5 and 6 of the book (which will be available as excerpts later) it addresses aspects of statistics that are particularly relevant to evidence-based (as opposed to subjective) technical analysis. full story

REGISTERED VIEWERS Genetic Programming (GP) is an appealing machine-learning technique for tackling financial engineering problems: it belongs to the family of evolutionary algorithms that have proven to be remarkably successful at handling complex optimization problems, and possesses the unique feature of producing solutions under a symbolic form that can be understood and analyzed by humans. Over the last decade, GP has been applied to generate financial trading strategies, forecast stocks and options prices, or grasp some insight into the dynamics of the markets and the behavior of the agents. In this paper, we first provide a brief survey of the existing studies, then highlight fields of investigations that, we believe, should lead to enhance the applicability and efficiency of GP in the financial domain. By Nicolas NAVET and Shu-Heng CHENfull story

FREE ARTICLEWe apply large deviation theory to assess the probability that a trading system performs below or above a certain threshold. Our technique does not require that the distribution of the performance criterion obeys a closed-form equation, and can accept as input empirical distributions given under the form of frequency histograms obtained by backtesting or from prior use of the trading system. A nice property of the technique is that it can be easily automated and integrated into a trading platform. Furthermore, the approach is not limited to a single trading system but can be applied on portfolio of trading systems. By Nicolas NAVET and René SCHOTT full story

FREE ARTICLEPart 2 of Pretests for genetic-programming evolved trading programs: “zero-intelligence” strategies and lottery trading bootstrap paper. By Shu-Heng Chen and Nicolas Navet full story

SUBSCRIBERS ONLYThis paper considers a generalised approach to the problem of rational value calculation of European options. A distinctive feature of the suggested approach is a rejection of the base asset market being described by means of standard price formation models. Only a relatively weak hypothesis connecting the base asset value with the market activity is imposed on the base asset behaviour. A generalised formula derived from this assumption describes in practice the behaviour of all options. By Vitaly Kurbakovsky and Dmitry Bourtov.full story

FREE ARTICLEIn recent years the landscape of trading venues has been transformed by technological ad­vances. New trading concepts and infrastructures along the securities trading value chain have been established. With RegNMS ("Regulation National Market System") in the US and MiFID ("Markets in Financial Instruments Directive") in the EU coming into effect in 2006 and 2007 respectively, regulators on both sides of the Atlantic respond to these changes. Both new legislations try to catch up with recent years' technological advances and intend to cre­ate a level playing field between the different types of trading venues and a harmonisation in the order execution process. Against this background, the paper illustrates and analyses the regulatory environments and the impact of their upcoming changes on ECNs and MTFs ("Multilateral Trading Facilities") – the European analogue of ECNs – with a specific focus on Europe. Based on the framework of market microstructure theory and the existing market structures, the paper will develop scenarios on how the upcoming regulatory overhauls and recent technological improvements will alter the competitive landscape between Regulated Markets, ECNs / MTFs and order flow internalising entities. By Peter Gomber, Markus Gsell Chair of e-Finance University of Frankfurt, Main full story

FREE ARTICLEThe correlation between historical and realized volatilities is studied empirically for a large range of time intervals. Similarly, the correlation between the volatility changes and the realized volatilities is studied. Both quantities measure the response functions of the market participants. These correlations show explicitly the heterogeneous structure of the market according to the characteristic time horizons of the different agents. It reveals a volatility cascade from long to short time horizons, with a structure different from the one observed in turbulence. A comparison is made with several theoretical processes used in finance, allowing to better understand the role and interactions of the market participants (intra­day trader, portfolio manager, central banks, pension funds, ...). Moreover, we have developed a new ARCH-type process that incorporates the different groups of agents, with their characteristic memories. This process reproduces well the empirical response function, and allows us to quantify the importance of each group. By Paul Lynch and Gilles Zumbachfull story