The application of advanced mathematics and statistics in the financial services sector is widespread. The Newton Gateway to Mathematics has developed a number of activities in this area, particularly for mathematical modelling and computational methods, working closely with industry stakeholders. The Gateway works as a delivery partner with the Cantab Capital Institute for the Mathematics of Information (CCIMI) on end-user engagement and interaction. CCIMI accommodates research activity on fundamental mathematical problems and methodology for understanding, analysing, processing and simulating data, including in the financial markets.
Upcoming Activities
Updates will be available in due course.
Previous Activities
Cantab Capital Institute for the Mathematics of Information – Connecting with Industry The main focus of this one day industrial engagement event was to provide an update on research and collaborations taking place at the CCIMI, as well as presenting interesting research being developed elsewhere. This event followed the previous industry and academic engagement events delivered since 2016 and more information is available on the Gateway initiatives webpage.
The Cantab Capital Institute for the Mathematics of Information (CCIMI) was pleased to announce its sixth annual academic conference, which focused on the academic advances in the mathematics of information. Uncertainty Quantification : Recent Advances in the Mathematics of Information, took place on 26th May 2022 and brought together those academics working to advance data science and provided an update on the research and collaborations taking place at CCIMI specifically related uncertainty quantification. Additionally, it highlighted other potential collaborative opportunities, as well as projects being developed elsewhere related to data analysis.
Cantab Capital Institute for the Mathematics of Information – Industry Engagement event took place on 24th November 2021. This conference brought together those academics working to advance data science and aimed to showcase the research that is being carried out at the Institute and enable delegates to hear more detail about some of the current project collaborations and industry challenges that CCIMI is exploring. Additionally, it highlighted other potential collaborative opportunities, as well as projects being developed elsewhere related to data analysis.
Privacy Enhancing Technologies in Practice took place as a series of short workshops- starting on 19th November 2020 and finishing on 19th January 2021.
Companies have been repeatedly told that data is one of their most valuable commodities, but realising the full value of that data may require re-mixing, comparison, or computation against data held by others. Unfortunately, sharing data is one of the hardest things for companies to do, because of the perceived commercial and legal risks. Even within a single organisation, sharing data can be considered to create large security or privacy risks.
Developed with academic partners and in collaboration with the Digital Catapult, these sessions recognised the need to help business and industry find effective ways to utilise these new privacy enhancing technologies.
Mathematics and Statistics for Effective Regulation took place on Tuesday 17th November 2020 virtually and in partnership with the Royal Statistical Society in London. The reliability and accuracy of reporting is key to ensuring confidence in the financial sector, yet there is limited regulation on data quality and the software used, a lack of consistency and no agreed documentation of modelling. This is in contrast to medicines and medical devices, where there are auditable processes in place with the requirement to demonstrate the source of data used and the need to show documentation of the workings of the software.
As well as providing a useful comparison of standards and approaches to regulation in the medical and financial sectors, this workshop provided an overview of the different expectations of regulatory bodies. It looked at approaches to assessing the quality and validity of data, statistics, computing and mathematics in the financial sector which differ substantially from those in the health sector. Speakers will explore these issues, with a focus on pensions, investments and fraud.
Mathematical Foundations of Optimisation in Data Science took place on Tuesday 24th November 2020 - the annual academic engagement event from the Cantab Capital Institute for the Mathematics of Information.
This one day conference brought together those academics working to advance data science and provided an update on the research and collaborations taking place at CCIMI, associated challenges and other potential collaborative opportunities, as well as highlighting projects being developed elsewhere related to data analysis. Talks covered the applications of optimisation methods in engineering and science; algorithm design, analysis and implementation for linear and nonlinear non convex smooth optimisation, regularisation and optimisation for machine learning. More details are on the event webpage.
IMA Mathematics 2020 Series Online took place in July. On 22nd July, Professor Jane Hutton spoke about Maths & Stats for Effective Regulation. This links to Mathematics and Statistics for Effective Regulation that will take place on Tuesday 17th November 2020.
The Future of Distributed Ledger Technology took place on Wednesday 6th November 2019. Distributed Ledger Technology (DLT), and its numerous potential applications, has gained increased attention in recent years. The UK showed early interest in the technology and through strong research effort is now recognised as a global player.This workshop was a collaboration with GCHQ, the Digital Catapult and the Engineering and Physical Sciences Research Council (EPSRC). In recognition of the potential and possibilities of DLT as a technology for both Government and the UK as a whole, it aimed to support appropriate use cases and promote research into scalable DLT. It also served to bring together stakeholders (researchers and end users) from multiple communities, to help connect people and build closer links and collaborations to strengthen the community.
"Verified Software" took place from Tuesday 24th September 2019 to Wednesday 25th September 2019, with VeTSS, the UK Research Institute in Verified Trustworthy Software Systems. This workshop comprised two days of talks by world-leading experts from academia, industry and government to help answer a number of questions related to the various challenges that exist in the verified software area. Its aim was to bring together verification, systems and security experts interested in formal analysis, industrialists interested in software validation, and government scientists interested in reliable software systems, and to introduce them to the current generation of UK PhD students and postdocs.
On Thursday 14th November 2018, TGM delivered the third Cantab Capital Institute for the Mathematics of Information – Connecting with Industry day. The main focus of this event was as an industrial engagement day that provided an update on research and collaborations taking place at the CCIMI, as well as presenting research being developed elsewhere.The talks highlighted research taking place at CCIMI, with associated industrial engagements and will look to explore the big questions in data science where mathematics is most suited to help provide answers.There was lso be a session hosted by CCIMI students which they developed and delivered as a group.
On 24th May 2018, the TGM delivered The Mathematics of Machine Learning - A Research Conference of the Cantab Capital Institute for the Mathematics of Information. This was the second annual academic conference from CCIMI and focused on the academic interactions taking place related to the mathematics of machine learning.
This one day conference brought together those academics working to advance data science and provided an update on research and collaborations taking place at CCIMI, associated challenges and other potential collaborative opportunities, as well as highlighting projects being developed elsewhere related to machine learning.
On 1st February 2018, the TGM delivered Taming Uncertainty in Mathematical Models Used in the Private and Public Sectors as part of the six month Programme at the INI on Uncertainty Quantification for Complex Systems: Theory and Methodologies. This event concentrated on how to handle uncertainty arising from the use of computer models and featured three end-user sessions including talks from the engineering, financial and healthcare sectors. These described how uncertainty is managed at present in a number of organisations and explored if we can cross-fertilise, for example, between engineering, finance and medicine.
On 22nd November 2017, the TGM delivered the 2nd Industry engagement day for the Cantab Capital Institute for the Mathematics of Information. The main focus of this one day conference event was as an industrial engagement day that provided an update on research and collaborations taking place at CCIMI, as well as highlighting projects being developed elsewhere. The talks will explored research taking place at CCIMI, with associated industrial engagements and looked at the big questions in data science where mathematics is most suited to help provide answers.
In collaboration with the Alan Turing Institute, the TGM developed and delivered a one day Algorithmic Trading: Perspectives from Mathematical Modelling event in London in March 2017. It aimed to disseminate the latest advances in quantitative modelling and empirical studies on the impact of HFT and algorithmic trading on markets, with an emphasis on emerging phenomena and implications for risk management and policy. Additionally, the talks and discussion session highlighted potential strategies which could mitigate against negative effects and risks of algorithmic trading in the future. A TGM case study about the event highlights the key challenges and opportunities of HFT.
In partnership with University College London (UCL), the TGM hosted Big Data Analytics for Financial Services on Thursday 7th January 2016 at UCL, London. This half-day event embedded within the UCL Theory of Big Data Conference, aimed to address some of these issues through a series of talks from leading industry and academic experts. The focus was on Big Data Analytics - the process of examining large data sets containing a variety of data types to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful business information. Presentations specifically addressed issues within the areas of systemic risk and financial regulation.
The 1st UCL Theory of Big Data Conferencetook place in January 2015 and included a half day TGM workshop, Coping with Big Data - an Analytics and Computational Perspective. brought together leading expertise in the areas of Big Data methodology, analytics and computation and provided an insight into the latest approaches and techniques needed to cope with this rapidly developing and important area.
In April and May 2015, the TGM hosted a series of 3 afternoon workshops Reasoning via Formal Models in Economics. This course of 6 lectures explored the purposes of mathematical modelling in the social sciences and illustrated them with examples from the literature. The talks were each given by Professor Sir Partha Dasgupta, FRS,FBA and Nobel Prize winning Professor Eric Maskin. The lectures were supported by the ESRC Impact Acceleration Account.
As part of the Isaac Newton Institute programme on Systemic Risk, the TGM developed and jointly organised an event with the Bank of England on Systemic Risk and Macro-Prudential Regulation: Perspectives from Network Analysis on 13th October 2014 in London.
In March 2014 the TGM ran a workshop on Mathematics for the Prediction of Financial Risk with speakers from Deloitte, Barclays and the University of Cambridge Statistics Laboratory, and the event carried CPD points from the Institute and Faculty of Actuaries and presented various state-of-the-art mathematical models for predicting financial risk.
