Credit Suisse has said that more sophisticated algorithms that handle unpredictability well, are key to achieving better execution.
The bank’s new Opportunistic Float algo is one of their most utilised algorithms in Asia and they say it can achieve worthwhile performance improvements.
“The difference between Opportunistic Float and our legacy algorithms is that the former relies heavily on market signals to take liquidity only when it is optimal,” said Murat Atamer, head of AES Product, Asia Pacific at Credit Suisse in Hong Kong.
“Its advanced optimizer that reads real-time market signals makes this algorithm’s behaviour very stock and order specific. This results in the algo being both stock and market agnostic. As such, it consistently outperforms other algorithms in every market over similar orders with similar completion rates against a number of commonly used benchmarks, such as arrival price.”
Numerous algorithms focus on predictability; a predictable algorithm being one that sells. However, Atamer believes that the taking away of such predictability may help performance considerably.
“We looked at the way our clients execute their orders and recognised how much our clients value the predictability of an algorithm,” he said. “Unfortunately, as comforting as predictability is, it comes at the cost of execution performance. As such, we have determined the need for a much more sophisticated algorithm that forgoes some of that predictability by trading in a much smarter way in both lit and dark markets via focusing on real-time market signals.”
Algorithms take instructions from a trader with that trader being the driving force. However, Atamer explained that advanced algos will take input from a trader, put it through market data and then decide whether to process it now or at a later time – when prices become more favourable. In difficult to trade markets, such as those often experienced in Asia, that can lead to a significant performance advantage.