How has the COVID-19 pandemic and subsequent market volatility encouraged the evolution of the trading analytics market? And what role will trade performance analytics play in this future?
- Trade performance analytics (TPA) is among the most valued technologies for traders looking into the future.
- The global COVID-19 pandemic and market volatility has increased the need for tools that bring more transparency for traders.
- TPA provides a transparent ecosystem for traders, quants and data scientists to view calculations and run them in a secure and scalable cloud-based environment.
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Until recently, most trading cost analytics solutions were static and optimised for post-trade reporting and not flexibility at the point-of-trade. Today, most solutions focus on post-trade, while some also offer integrated real-time streaming slippage benchmarks.
In a 2019 Greenwich Associates survey – produced in partnership with Refinitiv, an LSEG business – traders were asked which specific technologies will have the largest impact on financial markets over the subsequent three-to-five years.
TPA was ranked second by traders, just behind execution management systems, indicating the value that traders put on these analytics and their expectations for the future.
In 2021, a global pandemic and market volatility has evolved the need for tools that measure the trader’s ability to match, or beat, benchmarks to ones that help bring transparency and develop real-time insights to drive improved trading outcomes.
There is a new gap for a transparent trading analytics offering that is both transparent and designed to be extended by end-users directly.
TPA is open, flexible and powerful
Traders, quants, and risk professionals now need an agile platform that embeds standard analytics, like instrument-level statistics and execution benchmarking with the ability to integrate custom capabilities easily for orders and trades.
Our goal with TPA is to provide a transparent ecosystem for traders, quants and data scientists to view standardised calculations and also embed their own proprietary trading calculations and visualisations. In addition, they need to be able to run them in a secure and scalable cloud-based environment powered with Refinitiv data.
In rapidly transforming markets where pandemics, retail flows and cross-market spill-overs impact trading returns and risk, the ability to leverage the breadth of content across our APIs and link those analytics to your orders and trades during trading, makes TPA open and helps our clients unlock their ability to respond and win.
Python-savvy traders using TPA can immerse themselves and view or change calculations when they need to. Meanwhile, point-and-click traders do not have to sacrifice ergonomics in fast-moving markets. Both styles of intense interaction are supported.
TPA calculations recalculate in real-time in both Refinitiv Eikon and Workspace, and our standard-set of calculations can be extended by simple Python functions.
This means it is easy to integrate custom order-based analytics without having to invest time and energy in a compute platform. Traders see their calculations in their desktops as markets move, but all the calculations are hosted and permissioned in our secure cloud, freeing desktops from that burden.
TPA is built on the principle that analytics need to adapt to changing circumstances. Trading performance is tied to the ability to be flexible, and there are ever-expanding use-cases pre-trade and during the trade, not just after the trade.
Because TPA is developed around an open-architecture notebook metaphor, it provides more flexibility than static solutions for analytics, visualisations, and workflows.
TPA is a platform for customised trading analytics
TPA extends Refinitiv’s Data Platform APIs, which is powered by a rich set of trading analytics APIs as well as the notebook metaphor. Desk-aligned quants and other front-office personnel can augment the calculation suite, and traders can derive the benefits of trading analytics as part of a modern automated trading workflow with their execution and order management system.
TPA handles the complexity of entitlements and dependent data relationships. In this way, slippage and other calculations and visualisations are automatically recalculated and displayed as markets move.
TPA integrates with our Refinitiv REDI EMS and can display real-time streaming trading analytics on ticketed orders and their executions on Workspace and Eikon desktops using Codebook.
Codebook is our new re-imagined financial notebook. It is based on open-source Jupyter and has been extended by TPA for running Python-coded analytics with real-time performance inside Refinitiv’s market data and analytics desktop solutions.
TPA analytic capabilities and roadmap
Users have their workflow integrated with REDI EMS, so that as trades occur, traders can interact with the analytics blotter with order flow and trading analytics that automatically update in real-time. VWAP, Arrival and other execution slippage benchmarks update as the orders are worked and fills are received.
Currently, TPA can be used for benchmarking performance and optimising execution pre- and at-trade for equities (and limited futures capabilities) and comes standard with visualisations and analytics that automatically update as market conditions change. Some of the pre-packaged analytics include:
- Market impact, timing risk, and order duration estimates
- Instrument statistics (volatility, spread, ADV)
- Sector and industry classification breakdowns
- Execution benchmarks slippage (Interval VWAP, Arrival, Open, Previous Close)
By orchestrating the Python analytics into a notebook-based blotter, we make analytics more accessible for traders and easier to understand and action or modify. Meanwhile, by collecting, pipelining and distributing the analytics as a cloud-based service and removing the complexity of market data and order integration, we reduce the total cost of operating a comprehensive suite of standardised and custom trading performance analytics.
TPA analytics are calculated in the cloud, so that also reduces the load on desktops during peak periods. By removing the complexity of entitlements, data-mapping and UI-access, we make it easier to code and reduce the time-to-market of extending the environment with new analytical capabilities.
We expect to add new calculations and visualisations in 2021, including a more sophisticated market impact model based on machine-learning and intraday liquidity indicators as well as other trading statistics and classifications that impact intra-day trading performance.
We are also starting to work with early access customers to integrate more analytics and visualisations and deliver more self-service analytics.
Our solutions team can partner to help integrate TPA to other OMSs and EMSs and embed analytics and derived insights into your workflows in conjunction with our full launch later this year.