By Theo Hildyard , Software AG
@theohildyard

In the last few years, we’ve seen an increasing focus on the area of pre-trade risk in financial markets, particularly in electronically-traded instruments such as cash equities and exchange-traded futures and options. In fact, a number of regulatory bodies have introduced rules that specifically address this area, such as the US SEC rule 15c3-15, which requires brokers and dealers to have adequate pre-trade risk controls in place when accessing electronic markets.

While these rules are all well and good in that they do help to reduce the chance of “fat finger” errors or rogue algorithms disrupting the markets, most of these types of checks – even when things like position limits and exposure limits are taken into account – really only scratch the surface of what firms could be doing to effectively manage risk on a pre-trade basis.

Looking at this from a wider perspective, there are all kinds of questions that could be asked prior to executing a trade, where the answers would enable a much more informed go/no-go decision. The problem is of course that if you ask more questions – or if those questions become more complicated or draw on more data points – you are introducing longer delays between the quote/order and the trade itself.

The net result is that the way firms approach pre-trade risk often becomes something of a trade-off. Some, when faced with the challenge of assimilating ever-larger amounts of data from multiple sources and crunching the numbers, all within a short enough timeframe to not impact trading strategies, take the route of doing the minimum necessary to satisfy the regulations, so they can tick the required boxes and avoid being fined.

But pre-trade risk management is not just about avoiding penalties. It’s about identifying potential losses before trades are actually struck, so that appropriate action can be taken. This is easier said than done however, especially when operating within very short timescales.

The answer, as is often the case in today’s financial markets, lies in technology. More specifically, in-memory data management technology, which enables firms to bring together multiple sources of data from very large data sets, to enrich that data, and to perform complex calculations on that enriched data, all in-memory without continuous reads and writes to disk. Which means at very low latency, resulting in less of a trade-off as firms are able to do more calculations, with more data, in less time.

The more enlightened market participants, rather than just engaging in box-ticking exercises, are now starting to use this technology in a variety of ways to give themselves a much more holistic view of pre-trade risk, performing a far wider range of checks than was previously possible. Some are marking-to-market aggregated positions and open orders across multiple instruments based upon incoming market data and order flow. Others are using the technology to run complex credit valuation adjustment (CVA) calculations on-the-fly.

Some are even investigating how to perform firm-wide capital adequacy calculations on a pre-trade basis, which would never have been considered possible without the predictable, scalable performance provided by in-memory data management platforms.

This is the future direction of pre-trade risk management. Not just ticking the boxes that keep the regulators at bay, but using technology to provide a comprehensive, predictive, firm-wide overview of risk in real-time.