Algorithmic Trading and Risk

Algorithmic trading has grown substantially over the last few years, to the extent that there are now a number of Sell-side firms offering algorithmic trading strategies to their customers on the Buy-Side. But to keep themselves ahead of their competitors, the Buy-side firms who get involved in algo trading typically want customized strategies rather that the “cookie-cutter” algos that brokers offer to all of their clients.

So who are these Buy-side firms who want this customization? Hedge funds? Institutional asset managers?

Basically, it could be any Buy-side firm. From a small quantitative trading house with a couple of desk traders to a multi-billion dollar asset management firm. In fact, it’s often just one trader, or maybe a group of traders, at a big fund management firm who gets heavily into algo trading.

Typically, the algorithmic trading function is carried out in the front-office, or at least that has been the case to date. But increasingly, Sell-side firms are being asked by their clients to offer more risk management functionality, and to build things like pre-trade limit and risk checking directly into the algos themselves.

This is still a fairly new development however. Not many firms actually offer this yet. The brokers are still mainly playing the role of adviser regarding risk and analytics, and service provider regarding executions, allocation and clearing. Although the line dividing the risk management function on the Sell-side and the Buy-side is now becoming increasingly blurred.

Will demand grow for brokers to provide such services? That remains to be seen. There is of course, the whole regulatory question, in terms of who is responsible for what. The brokers on the Sell-side can provide advise regarding implementation but when they offer advice regarding investment, then there is some very strict regulation around that in terms of what they can and can’t do.

With the growth in algorithmic trading, it is likely that new regulations will come along regarding risk.

For more information, visit the Algorithmic Trading Podcast