Electronic trading will continue to shape our industry’s future, delivering speed, scale and embedded compliance that provides a competitive edge. But from here on in, it’s not only the automation that will shape the future.
In the 2020s, the broader application of newer, more advanced technologies will underpin the endeavors of the buy-side trading desk.
Thanks to the exponential advances in machine learning and analytics’ visualisation, algorithmic trading technology has almost reached an infinite level of customisation. Savvy brokers and their algo development partners can conceive and create increasingly sophisticated and high performing execution strategies in an agile manner. The era of bespoke booking is back, with or without high touch, but with much greater efficiency.
So how does the buy-side best equip itself to leverage these solutions?
Today’s SaaS trading tools provide the most robust and scalable option to facilitate the following capabilities:
Plan, backtest and analyse: Next generation tools and platforms enable traders to efficiently extract vast samples of the historical tick-by-tick data and even real-time analytics for backtesting and research. It is, therefore, possible to predict how a proposed trading strategy behaves over different market cycles to help determine long term profitability. Such insights can help generate custom and interactive real-time visualisations to reveal opportunities more intuitively.
Design, develop and deploy: With open-source API’s, traders can convert their trading insights into custom strategies and connect their unique algorithms to a SaaS deployed trading networks such as TS, and trade across all markets and asset classes via one connection. Through integrated compliance engines, the challenges of an increasingly complex regulatory landscape can be swiftly navigated allowing order flow to reach the desired counterparty, liquidity provider or venue as seamlessly and efficiently as possible.
Monitor, adapt and execute: A flexible workflow, supporting both solicited and unsolicited order generation requires a fluid interconnection between the OMS and the EMS, which often has not been the case. This interplay not only enables engagement with disparate and diverse data sources and multiple trading protocols but also real-time execution reporting and analytics which can be fed into the pre-trade decision-making loop.
In summary, TS, with its pre-certified all asset class connectivity, open SaaS architecture and fully integrated data model provides the optimal platform for the buy-side. It is able to leverage TS’ pre-canned referential data, flexible range of live market data and streaming price feeds together with an out-of-the-box historical database to generate its own custom indicators and proprietary trading strategies. These content and functionality-rich capabilities all contribute to the buy side’s central objectives of best execution, the maximisation of operational efficiencies and the reduction of TCO.