Execution management system (EMS) provider, Wave Labs, is launching its Systematic Investment Application (SIA), a new modular system for developing systematic strategies in the corporate bond space, in May 2022.
“Expecting portfolio managers (PMs) and traders to code in order to work with data is an old school way of thinking,” says Miles Kumaresan, CEO of Wave Labs. “Technology solutions are the ones that should adapt to empower domain specialists. This is exactly what SIA offers – it translates high level ideas of PMs into program code and machine learning models automatically, allowing these domain specialists to explore investment ideas independently. This is truly powerful.”
The objective was to create a general purpose, domain-specific technology that would allow portfolio managers to test and explore investment ideas and then over time, put them together into a standalone strategy.
“One cannot not go from nothing to systematic investments in credit overnight,” says Kumaresan. “It is an evolutionary process, starting with PMs exploring data, then moving on to testing various investment ideas, and then finally picking a set of the better ideas to form a systematic investment strategy. This takes time but this is also what is needed to create stable investment strategies.”
To offer people who generally do not code a way to mine data and evaluate complex ideas, Wave Labs’ has approached the problem with a visual no-code solution, to support PM in constructing ideas visually combining building blocks and parametrising. PMs will have the ownership and intellectual property (IP) rights of these investment ideas.
Herleif Haarvik, who has joined Wave Labs as an advisory board member, “What we want to create is a feature we find most systems lack – an idea generator. It is a thankless task for any credit analyst or portfolio manager to keep on top of changes in thousands of bonds. Wave Labs’ SIA will help with this by systematically comb a given universe and highlight bonds that most likely will move soon.”
By working either as a standalone tool or integrated with Wave Lab’s electronic liquidity seeking application (eLiSA) suite, Kumaresan argues traders and PMs can better support an understanding of trade execution costs in the context of investment goals.
“With credit in particular, investment ideas whether they are systematic or otherwise, all hinge on the impact of trading cost. Therefore, exploring investment opportunities in tandem with execution cost is critical for success,” he says. “While we have a trading cost framework, we will work in collaboration with head traders out there to fine tune this – trading cost is not a one-fit-all, it is a function of trading horizon, expectations, constraints, who, etc.”
©Markets Media Europe, 2022
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