Maximising Our Buy-side Skill-sets


By Neil Bond, Equity Dealer, Ardevora Asset Management
The buy-side has made huge leaps forwards in the last five or six years –their reliance on the sell side has reduced and now they are using the same tools and skill sets as the sell-side, and this is why a lot of people are moving across to the buy-side; control of trading is moving in-house. There are lots of things that have led to this – mergers in banks and money managers have led to much bigger orders flows through fewer partners – more program desks used algos with higher rates, so algo control moved to the buy-side to manage that cost, but they had to acquire the skills and people to monitor the trading with algos and to do the analytics pre- and post-trade. The consolidation of money managers and brokers led to a growth in program trading which in turn led to the proliferation of algos. As the buy-side squeezed the sell side on costs, the responsibility for algo use moved to the end user. With this responsibility comes the need to understand the tools you are using, not just the algos themselves, but the pre and post trade analytics too.
When orders hit the blotter I have already got the capabilities to analyze order characteristics – expected market impact and %ADV etc and I can use that information to slice and dice the flow into different strategies. The easy stuff can go through a vanilla strategy – VWAP, TWAP etc and the trickier stuff we can work ourselves according to the best strategy – IOIs, who has been trading the name, and trying to find a more sensible way to do the trades. We do like to use a lot of the dark pools for that as the anonymity levels the playing field between small and large players. We also split orders over different dark pools to find liquidity and minimize impact. We use in-house tools to monitor performance throughout and after a trade, and we look to see what we can do better and why. And we use 3rd party TCA tools to analyse trades over a longer period, particularly for peer comparison.
Ardevora funds are just over three years old and have recently surpassed the $1bn mark, so we are a relatively small firm but we are able to leverage technology, either in house or provided by brokers, that closes the competitive gap with larger firms greatly. We use Bloomberg AIM as it has multiple tools that you need for trading, and it also gives you what you need with regard to pre-trade analytics, and during the trade it can monitor performance and do post-trade analytics and TCA. Those tools help massively, and our size is often not a problem as a large proportion of our trades are executed anonymously in dark pools.
The biggest difference between small and large firms is the extent of bespoke automation of trading and monitoring. However there is a lot that we can achieve without a high level of customization.