Automated Trader Magazine Issue 08 Q1 2008

Automated Trader Magazine Issue 08 Q1 2008

Automated Trader starts 2008 with an optimistic story of expansion and growth. This might seem somewhat at odds with very real concerns about reduced liquidity in the financial markets and lower incomes and spending in the wider economy. But this first issue of 2008, which also marks our second anniversary (see page 54 for Managing Director Andy Webb’s review of upcoming developments at AT), reflects the sheer diversity and dynamism of automated and algorithmic trading, and the ways in which it is bringing greater efficiency to the financial markets. We are still some distance from, and may never reach, a state of equilibrium in which humans and machines are accorded the tasks in the financial markets to which they’re best suited. This issue nevertheless pursues that path across asset classes, geographies and technologies.

Though automated and algorithmic trading originated in and now increasingly dominates trading activity in exchange-traded instruments, its application in foreign exchange – an asset class singularly lacking in formalised exchange structures – has been a fascinating one. In ‘Buy Side Flocks to FX’, we look at the different automated trading models and execution algorithms that are proving most effective in an increasingly competitive market (page 50). Meanwhile, Dr Usman Malik of P.E. Lynch LLP considers the geographic expansion of algorithmic trading in an article which emphasises the importance of adapting to specific market conditions, in this case Asian, to optimise trading performance (page 20). The globalisation of algorithmic and automated trading is a theme also taken up by Gary King, CEO of the Dubai Mercantile Exchange, in this issue’s leader, which reviews developments in the Middle East, one of the most dynamic and fastchanging trading sectors in the world (page 12).

An innovation for this issue, designed to fulfill reader requests for practical ‘how to’ content, is Anatomy of an Algo (page 47), a new regular column in which we explain how different types of execution algorithm conduct common trades across various market conditions. At the other end of the spectrum, David Aronson explores how advanced modelling techniques, such as kernel regression, can be utilised in the creation of performance boosting models (page 16). This issue’s AT interview, with BlackCat Trading Technologies, provides a link between these articles by exploring the path from casual interest in rules-based trading to designing and utilising a sophisticated trading platform. While the short-term forecast may be uncertain, the pace and breadth of innovation in algorithmic and automated trading is reason enough for an optimistic long-term outlook.

Chris Hall - Editor Issue 08

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