Trade Data Analysis
Since inception in 2010, TradingHub has been providing trade data analytics to the financial services industry with clients ranging from international banks and asset managers to regulatory institutions. Our performance matrices are based on methodologies comprising a set of unique metrics and analytic processes that enable our clients to:
- objectively assess and improve the performance of their traders,
- identify trader actions that may constitute market abuse or rogue trading or/and
- analyse execution quality.
These state-of-the-art metrics-based systems identify, investigate and report market abuse (MAST), unauthorised rogue trading activity (RTMS), analyse best execution and off-market trades (TEAM) and behavioural and performance profiles of traders and PMs (PM/Trader Profiling) across any instrument type and asset class.
We have developed a metrics based system to identify, investigate and report unauthorised trading activity. This product is called the Rogue Trader Metrics System (RTMS).
RTMS identifies traders who are hiding or obscuring risk, P&L and/or otherwise engaging in unauthorised trading activity irrespective of asset class, instrument type or trading venue. RTMS can process global enterprise levels of data accurately and efficiently.
RTMS uses a red flag system to indicate incidences of potential breach and asserts a level of confidence that is based upon its proprietary scoring method. This method provides clients with clear priority based grounds for further investigation.
RTMS includes an integrated case management system that enables client risk, compliance and audit functions to investigate potential breaches, document follow up actions and generate audit reports.
The Transaction Efficiency and Accuracy Monitor (TEAM) allows users to compare trades across brokers and venues to assess which deliver best execution. TEAM employs sophisticated quantitative techniques that are unlike anything else on the market. In common with our other products, it works across all asset classes and product types, ingesting and analysing global volumes of data.
With machine learning algorithms at its core, TEAM creates a probability distribution for the mid-price of any asset at any time in the past. The tool then compares the client’s executed trades to this distribution, permitting the user to measure the performance of their broker against the market – even for relatively illiquid assets. Despite the sophistication of this analysis, TEAM’s clear interface ensures that understanding the results is simple and efficient.
Buy-side and Sell-side
TEAM has benefits for both the buy-side and sell-side. While buy-side users may use the tool to assess the performance of their brokers, so too can users on the sell-side compare themselves against their peers. The tool is flexible, scalable and brings value to all firms throughout the market.