Market Quality Dashboard

The Market Quality Dashboard is a software product from the Capital Markets Cooperative Research Centre (CMCRC) designed to allow market participants to quantify the economic impact of market design changes on market quality. Market quality is defined by reference to the near universal mandate of regulators, which seeks to ensure that markets are fair and efficient.  It therefore follows that, if one intends to change the design of a market place, and get this signed off by regulators, those changes are evaluated in terms of how they impact fairness and efficiency. The MQ Dashboard arrays all market design changes in a market place and provides a series of user chosen metrics representing the concepts of fairness and efficiency. Using time series visualisations, users can identify changes in metrics for the better or worse,  pre  and  post  the  market  design changes of interest. The MQ Dashboard technology is web delivered and easily accessed with a standard browser and a username and password that dictate the level of data/metrics that particular users can view. There is no need for software onsite and secure websites can be set up for each user. The MQ Dashboard allows users to choose a number of parameters for their unit of analysis, such as individual stocks in a marketplace, user-driven stock groupings, event study, customized metric. In future iterations, cross-listed stocks analysis, automated control sample will also be provided.  

Financial Market Data ETL Workflow Engine

On a daily basis, the CMCRC extracts, transforms and loads (ETL) financial market data for over 50 global markets, which serves as the vital input to the research program and product development such as the Market Quality Dashboard. In order to maintain processing efficiency and data quality at high level, the CMCRC developed a unique ETL Workflow Engine that has automated data management and outlier detection to the maximum extent. The ETL Workflow Engine seamlessly supports cluster and cloud computing.

Natural Language Processing

Traditional finance research has primarily been based on structured numerical data mainly due to the difficulty with mining unstructured text. The CMCRC developed CompNews aiming to unlock knowledge from this via entities – the companies, people, places and locations that the text is about. The system provides a “computable” layer of structured data over unstructured text, giving user a platform on which to build advanced analytical applications for information leakage detection and research on social media’s impact on financial markets.  

Alluvial Backtesting Platform

Alluvial is a new software product from the Capital Markets Cooperative Research Centre (CMCRC) offering algorithmic back-testing and trading solutions to advance the research, development, implementation, and evaluation of automated trading strategies. Financial markets are becoming increasingly technology driven. High frequency and algorithmic trading not only overwhelmingly reforms the finance industry, but also poses evolving challenges to market regulators. Algorithmic traders require substantial infrastructure and specialised skills to find trading patterns from BIG data as well as automated trading software to exploit high frequency patterns. On the other hand, the “flash crash” in 2010 has urged market regulators to evaluate how an algorithmic trading strategy is going to impact market quality (efficiency and fairness) before it is adopted. Alluvial provides an integrated solution for both user groups. The Alluvial system is client-server software with web accessibility. Advanced users, who require direct connectivity to their market data feed and dedicated line for order submission, can have the software deployed onsite. A web portal may also be provided for users to access the Backtester, Compliance manager and inventory manager remotely. For general users who may only wish to access the Alluvial Backtester, a lite version of Alluvial which operates as a hosted service is currently under being developed.

Uptick – 4GL Language for Market Data Analysis

In order to enable non-IT users to develop their own back-testable trading algorithms and market quality metrics, the CMCRC developed the UPTICK language, which is the core component of the Alluvial Back-testing Platform. UPTICK is a python based 4GL language. It uses more readable and simplified syntax and has a large number of common financial market concepts and trading attributes (such as true price, spread, VWAP) as inbuilt functions. Users will be able to submit metrics and algorithms developed in UPTICK to the CMCRC infrastructure for processing and visualisation.


The CMCRC’s founder Professor Michael Aitken also founded SIRCA. Working together with SIRCA, CMCRC built the first prototype of the Thomson Reuters Tick History Service (TRTH). TRTH comprises intraday trade quote and information announcements (in milliseconds) for every securities market in the world. CMCRC’s 50% share of the IP in TRTH (then known as the RASP) was transferred to SIRCA at no cost to ensure that SIRCA was able to sustain itself and in the process provide highly subsidised access to the TRTH resource to its academic constituency comprising more than 40 universities. Today this facility underwrites more than 1,000 pieces of research per annum many of which emanate from Australia researchers significantly increasing the research output of Australia vis-à-vis the world.  

Capital Markets Surveillance Services Pty Ltd (CMSS)

Capital Markets Surveillance Services Pty Ltd (CMSS) markets and supports a broker compliance product known as Compliance Explorer. Compliance Explorer is the first simultaneous, real-time cross market surveillance system developed for the compliance manager and staff of brokers. Motivated by several requests from international broking firms for a global compliance solution, CMSS combined the industry expertise of SMARTS Pty Ltd and leading academic research from CMCRC to produce a product which assists brokers in protecting their reputation from financial and/or regulatory risks, and indirectly to protect the reputation of the market. Learn more: