March 2013 - sponsored by: Azul Systems, OneMarketData
The extent to which algorithmic trading has permeated the financial services industry depends on who you ask. Take, for example, a traditional, equities-only "pick-and-stick" asset manager, which typically employs lengthy investment horizons, and therefore, may only execute a small number of orders during the course of a normal month. Shredding large block trades into smaller child orders as a way of increasing the likelihood of obtaining a fill and reducing market impact and diversifying risk, is not something long-only shops are interested in. But scratch under the surface of a more "adventurous" buy-side entity-any firm that executes large numbers of trades during the course of a typical trading day-and you'll find a small army of home grown, broker-provided, or third-party-developed algorithms hard at work, responsible for determining when to trade, where to trade, how to trade, and how often to trade. This might sound highly sophisticated, but in truth, the market's forerunners have been doing this sort of thing for at least the past decade.
What has changed in recent years, however, is the extent to which providers-both brokers and specialist third-party vendors-have "parameterized" their offerings, allowing users to tweak their parameters on-the-fly, effectively changing the algorithm's behaviour without affecting its core logic. This means that in the event that traders believe market conditions have changed from what they were when the algorithm was initially deployed-which can undermine the algo's efficacy-they can modify any number of parameters, thereby maintaining its level of specificity and effectiveness. In the past, end-users were most often forced to rely on their algo developers to make the necessary tweaks, a process that was both long-winded and laborious. In the algorithmic trading roundtable on page 4, there is frequent reference by our four panelists to the importance of parameterization, and the extent to which it allows buy-side and sell-side practitioners to differentiate themselves in what has become a crowded and highly competitive space.
Rich Newman joins to talk about challenges facing the alternative data space and why open data is becoming increasingly important.Subscribe to Weekly Wrap emails