Project code



School of Accounting, Economics and Finance

Start dates

October 2023

Closing date

6 April 2023

Applications are invited for a fully-funded three year PhD to commence in October 2023. 

The PhD will be based in the Faculty of Business and Law, and will be supervised by Dr Alexis Stenfors, Dr Paraskevas Pagas and Dr Michail Filippidis

Candidates applying for this project may be eligible to compete for one of a small number of bursaries available. Successful applicants will receive a bursary to cover tuition fees for three years and a stipend in line with the UKRI rate (£17,668 for 2022/23). Bursary recipients will also receive a contribution of £2,000 towards fieldwork. In addition, the Faculty supports conference costs with a contribution of £550 and training costs with a contribution of £450.

The work on this project could involve:

  • To study the mechanism and speed of shock transmissions across financial markets and trading venues.
  • To investigate into the link between liquidity provision, electronification and systemic risks in OTC markets.
  • To design and test a methodology to detect market manipulation.

Money, bond and foreign exchange markets are generally traded over-the-counter (OTC) instead of on exchanges. However, recent developments in financial technology have dramatically changed the OTC landscape and resulted in an array of new electronic trading platforms and an influx of algorithmic and high-frequency traders and liquidity providers. This research project aims to deepen our understanding of how global OTC markets have changed due to increasing electronification. The project addresses three topics:

First, OTC markets are more interconnected than other markets. Moreover, financial crises typically originate in OTC markets. The project seeks to explore how and how fast shocks are transmitted across markets and trading venues – and the implication on crisis mitigation.

Second, liquidity in OTC markets has historically been provided by human traders at market-making banks. This convention has gradually been eroded by algorithmic traders not bound by traditional structures and relationships. However, concerns have been raised that algorithmic traders will disappear as soon as liquidity is needed the most. The project investigates the link between liquidity provision, electronification and systemic risks.

Third, recent regulatory reports suggest that the “rise of machines” has resulted in an increase in sophisticated strategies of market manipulation that benefit from the ability to submit and cancel orders across markets and trading venues. The project includes a detailed exploration into the design of genuine as well as illegal trading strategies and surveillance methodologies aimed at detecting anomalous or potentially unethical trading behaviour. 

This research project builds on recent and current work on OTC markets. It makes use of novel datasets, state-of-the-art methodologies and an international cluster of experts from academia and the financial sector. Ultimately, the project seeks to guide policymakers, financial regulators, compliance and surveillance departments so that the proper mechanisms are put in place to safeguard the international financial system and protect market participants, corporations and the wider public.

Entry requirements

You'll need a good first degree from an internationally recognised university (minimum upper second class or equivalent, depending on your chosen course) or a Master’s degree in an appropriate subject. In exceptional cases, we may consider equivalent professional experience and/or qualifications. English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

A desirable academic background includes Finance, Economics or a quantitative subject (e.g. Mathematics, Computer Science, Data Science) with a strong emphasis on finance. Experience, expertise or a passionate interest in financial markets in general, and OTC markets in particular, is a must. In addition, evidence of programming (e.g. Python, Matlab) or experience in machine learning would be a significant advantage.


How to apply

We’d encourage you to contact Dr Alexis Stenfors ( to discuss your interest before you apply, quoting the project code.

When you are ready to apply, you can use our online application form. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV.  Our ‘How to Apply’ page offers further guidance on the PhD application process.

Please also include a research proposal of 1,000 words outlining the main features of your proposed research design – including how it meets the stated objectives, the challenges this project may present, and how the work will build on or challenge existing research in the above field.

If you want to be considered for this funded PhD opportunity you must quote project code AE&F8070423 when applying and submit all required documentation.