Dr Vu Tran
Accounting & Finance
Telephone: (01792) 513130
Room: Office 229 - 229
Second Floor
School of Management
Bay Campus

Dr Vu Tran is a Lecturer in Finance in School of Management at Swansea University. He has joined the School since January 2015. Previously, Vu worked as a part-time research assistant, tutor, associate lecturer in Bangor University and Northampton University. Prior to coming to the UK, he worked for Ministry of Finance in securities, investment, and finance regulation for five years.

He has published on International Review of Financial Analysis, Economic Notes. Vu is interested in supervising PhD students in following topics: credit risk, credit ratings, volatility modelling, banking stability, price discovery process, high-frequency finance and market microstructure.

Honours and awards: Bangor University 125th Anniversary scholarship for the PhD study, Bangor University Gold scholarship for the MSc course, Centre bank’s scholarships for excellent performance in Undergraduate course.

Conferences and seminar presentation: Adam Smith Business School, University of Glasgow (August 2014); Gregynog Accounting and Finance Colloquium (May 2014); Bangor Business School Browbag Research Seminar (May, 2014).

Ad-hoc refereeing: European Journal of Finance, International Review of Financial Analysis, Studies in Nonlinear Dynamics and Econometrics, Eurasian Economic Review.


  1. Fan, R., Talavera, O., Tran, V. Social media bots and stock markets European Financial Management
  2. ap Gwilym, O., Alsakka, R., Tran, V. Investors’ heterogeneous beliefs and the impact of sovereign credit ratings in foreign exchange and equity markets The European Journal of Finance 1 23
  3. Tran, V. Market Impact under a New Regulatory Regime: Credit Rating Agencies in Europe Economic Notes 44 2 275 308
  4. Tran, V. Sovereign rating actions and the implied volatility of stock index options International Review of Financial Analysis 34 101 113


  • MN-3501 Financial Economics

    This module aims to provide students with a detailed understanding (mostly theoretic foundations) of portfolio theory and the relationship between risk and return from an investment, and of specific models designed to study the relationship between risk and return. This module requires a high level of mathematical ability (e.g. optimisation, basic linear algebra, advanced statistics and time series econometrics).

  • MN-M584 Big Data in Finance

    Big Data analytics is increasingly desired by various businesses in today¿s data-driven landscape. The main goal of this module is to provide students with skills in collecting, handling, managing, analysing and making initial inferences in the process of discovering patterns in large data sets. The data management and statistical software used in this module are all very useful for prospective jobs in Data Analytics in Finance, Business, and other industries.


  • the effects of sovereign credit rating on firm behaviours (current)

    Student name:
    Other supervisor: Dr Vineet Upreti