"Our aim is to turn the process of product development and execution consulting on its head - making our platform client-centric and more immediate"
UBS today announced the launch of a new algorithmic trading tool called "UBS QUOD Studio." The launch is part of the Swiss bank's execution consulting service called UBS Quant on Demand.
UBS QUOD Studio is an iPad app allowing UBS algorithmic trading team members to collaborate with clients to rapidly design, simulate and develop execution strategies for trading in the securities markets.
"Our aim is to turn the process of product development and execution consulting on its head - making our platform client-centric and more immediate." said Owain Self, Global Head of Algorithmic Trading at UBS. "The first tool we are launching in this family is 'UBS QUOD Studio' - an iPad-based application that delivers a next-generation, rapid algorithmic development framework. UBS Quant on Demand will, over time, deliver a series of highly sophisticated and automated quantitative, consultative and personalized solutions to clients 'on demand'.
The proprietary interactive iPad app allows the UBS algorithmic trading team to work with clients to design and build custom strategies that fit their specific workflow, view of the market, and individual objectives. UBS claim a rapid turnaround offering the potential for clients to deploy their strategy the next day.
Phil Allison, Global Head of Cash for UBS, said: "What makes QUOD Studio unique is that UBS is custom fitting our technology to meet client needs, not vice-versa. Traders can simulate performance of algorithms before they build them - so they can try "what if" scenarios to see how the outcomes may change when various components and triggers are changed."
Traditional custom algorithmic development process can be time and resource intensive. If the UBS initiative to help clients shorten the development process and time to market proves successful it will no doubt become a popular feature amongst clients. "Having to re-engineer models to keep them profitable" was a key challenge cited by over 40% of buy-side respondents in Automated Trader's recent Algorithmic Trading Survey. At the same time, ever shortening model half life increasingly forces traders to focus on strategies that serve a very specific short-term need, or strategies that fundamentally alter the way they trade given certain circumstances.