Regulation today is having a profound influence on the global business landscape. Many of the stories in today’s news are about market volatility, fragmentation and difficulties facing today’s financial markets including whether regulation has helped or hurt in improving the economy in the face of the global financial crisis. Amidst the chaos, one regulation in particular, is bringing about innovation and new business opportunities – in Chicago.
The Volcker Rule, which is part of the larger Dodd Frank Financial Reform Act, bans the practice of proprietary trading at banks. As such, as banks now have to dispose of this arm, proprietary trading is finding a new home; these traders are fleeing banks to set up small, independent proprietary trading companies. They have money under management from outside investors, and they are trying to make money for themselves which brings a new level of engagement to the investment strategy process.
New Firms; New Strategies
The first challenge for these new, small proprietary trading shops is going to be how to make the transition from defining strategies for a large bank to a small firm. Is high frequency trading, algorithmic trading or another strategy the way to go?
We all know that the problem with high frequency trading today is that the speed required to be competitive makes it a game for only the fastest technology holders. Some say that anything over 500 microseconds is subpar, and to really be competitive, a system needs to be in and out of the marketplace within 80 microseconds. To keep up with that speed, the strategies for high frequency trading cannot have too many steps because each new step needs to be mapped and thus slows down the process, introducing more latency. For that reason, high frequency trading strategies tend to be quite similar and are typically straight-forward enough so that by now, everyone has the same one. The only way to make money with high-frequency trading is to be first to market, which means updating your technology frequently to remain competitive. The cost barrier to entry is so high that only a select few can make money by using it.
It is within the space of algorithmic trading that there is a real opportunity to lay out a competitive advantage. Algorithmic trading is still plenty fast, but it does not match the high speeds found in true high frequency trading. Being fast, but not needing to be too fast, leaves enough room to employ creative strategies that liberate these proprietary trading firms from the race to be first to market.
Setting up a New Proprietary Trading Shop – in Chicago
This wave of new firms is not naïve for starting new businesses in this type of economy. These individuals are well-versed in electronic trading; they are just replicating their models for success in a different environment. They are made up of confident investors and talented people from top universities who are building on the established investment community in Chicago.
Historically, in Chicago’s proprietary trading shops, there has been a larger trend towards options trading than in other regions. This is, in part, due to derivatives traders in Chicago that left the floor of the exchange to set up their own electronic trading shops. Most of the existing proprietary trading firms in Chicago today started out this way. Some were purchased and rolled in to bigger institutions, and now, as the Volcker rule forces banks to disband their proprietary trading groups, we see that wave continuing as these firms go out (or go back out) on their own. They are creating a new wave of innovation and demand for high volume trade data analysis to develop new strategies.
To develop these strategies, these firms need a high speed database that their quants can use to effectively manage large volumes of data. When considering data volume, there is a hierarchy based on the asset class. Treasuries require the lowest volumes of data, followed by fixed income, then equities and finally equity options. As Chicago has a lot of futures and options traders, those asset classes represent huge data sets and the ability to model scenarios using that data is a key differentiator that firms will need to set-up the event-based processing scenarios needed for algorithmic trading.
A Volume-Driven Need for Speed
These new companies are keenly aware of the need to develop an infrastructure scalable to large data management capabilities and able to handle an equity options infrastructure. Given the hierarchy of data sets, the new proprietary trading shops in this region are running more data volumes than anywhere else. On average, clients are loading upwards of half a terabyte of data per day. There are small shops loading massive amounts of data whereas in New York and other cities there are big shops loading average amounts of data.
With quant traders as CEOs, the people making the decisions are the people using the platform. As such, in this new proprietary trading shop, the roles of the technologist and the trader have merged – people making the business decisions understand the technology. And, they can capitalize on the advantage of being able to act more quickly as a smaller firm because they don’t have as much red tape for budgeting and approvals. These firms are poised to define strategy for the industry and develop the region into a powerful microcosm of trading innovation.
Fintan Quill is a senior pre-sales engineer at Kx Systems