EU-China Cross-Border Investments Project

Context and vision: 

Over the last decades there has been a substantial increase of both Chinese foreign direct investment (greenfield, M&A) and portfolio investments in Europe, and of European investments in China. These trends in EU-China cross-border investments pose several fundamental and applied financial research challenges which we aim to address within this project.

Applied research: 

The objective of this project is to attract funding to build a joint capacity of collecting and diffusing data on the evolution of the EU-China cross-border investments (both aggregate and at the more granular levels of sector and country), and of the drivers of investments (performance, risk, policy, exchange rates). Besides providing an easily accessible interface to the relevant data, the aim is also to publish on a regular basis the applied research results. These white papers will need to discuss the evolution in monitored statistics as well as present-day interview-based case studies of EU-China cross-border investment decisions. As such, this strand of applied research will contribute to the creation of a more fact-based image of the impact of Chinese investments in Europe and of European investments in China.

Fundamental research:

In terms of fundamental research, the EU-China cross-border investment project aims to develop statistical methodologies and mathematical models to improve the EU-China cross-border investment decision-making from both an individual investor’s perspective, the institutional investor’s perspective as well as the macro perspective. The approach needs to take into account the differences in utility functions (i.e. the objective functions considered) between European and Chinese investors, the specifications of available data, the types of investment and the differences in the economic and financial market structures. Models will need to take into account and explain the sources of non-normality and non-linear time series and cross-sectional dependence. Based on these models, the project aims to propose a framework to optimise the financial decisions and evaluate the quality of the decisions.