Research themes

Firm Behavior and Performance

This theme investigates key aspects of firms’ strategic decisions and their aggregate economic implications using large micro datasets, answering questions such as how firms price their products and compete in the global and local markets, how firms manage their supply chains and interact with their business partners, and how firms grow by upgrading their technologies or expanding to new markets. A key area of research is to understand how answers to these questions change under different market conditions and economic shocks. Recent research focuses on the impact of COVID-19, studying firms’ price and production decisions during the COVID-19 outbreak, investigating how firms’ responses to the crisis differ depending on their characteristics and quantifying the aggregate implications of these responses.

Economic Policy Analysis and Evaluation

Within this theme, members investigate and evaluate the impacts of monetary, fiscal, trade and industrial policies on economic outcomes. Recent policies and events analysed include the impact of training programs and grants on firm and labour market outcomes, the effects of innovation policies, as well as recent trade policies and the effects of Brexit on UK exports. Such research leads to substantial impact by evaluating specific policies and formulating recommendations for policy makers.

Big Data and Machine Learning in Finance

Thanks to the massive size of financial data and even growing computational power, applying machine learning techniques in finance is becoming more popular and rigorous. Our projects under this theme include but are not limited to: portfolio management using estimation; error minimisation via machine learning; algorithmic trading exploring systematic miss-pricing via machine learning; account information fraud detection using textual analysis and machine learning; high dimensional risk management using machine learning.

Big Data Analysis for Business and Management

One important domain which big data technique can be applied to is business and management. The insights derived from the big data analysis can assist various sizes of firms, along with policy makers, to make well informed strategies and accurately assess the business outcomes. The typical big data in this area includes the data at operational levels such as sales, cost, R&D expenses etc. In addition to this actual data obtained from firms’ daily operation, some statistical simulation exercises, many key parameters of which are collected from the real world, can also be implemented to enlighten the critical business decisions.

Econometrics and Big Data Methods

Within this theme, members engage actively in the forefront of theoretical and methodological research for modern econometric and big data analyses. We have internationally leading and excellent research expertise and publish in areas broadly including: Bayesian and machine learning methods, semi- and non-parametric techniques for high dimensional or high frequency data, and time series analysis techniques for modelling structural stability, regime switching, dynamic dependence, as well as continuous time stochastic processes and count data.