Skip navigation
Please use this identifier to cite or link to this item:
Title: A Macroeconomic-Based Risk Management Approach to Assessing the Credit Risk of Real Estate Companies in China
Authors: Chen, Sophia
Advisors: Mulvey, John
Department: Operations Research and Financial Engineering
Certificate Program: Applications of Computing Program
Class Year: 2019
Abstract: Over the past decade, the Chinese economy has experienced spectacular growth, largely fueled by the Chinese real estate market. The rapid development of the real estate industry has given rise to two alarming trends in China: enormous housing price appreciation and soaring distressed corporate debt. This accumulation of distressed credit has hit debt-laden Chinese real estate developers particularly hard, resulting in a significant increase in default risks among such firms. However, it has proven difficult to assess and predict these default risks, since standard risk measures and market indicators may not be reliable in China due to market imperfections. We test this assertion by formulating our own macroeconomic-based risk factor model for listed Chinese real estate companies. We find evidence that there is a lagged correlation between the Shanghai Stock Exchange’s real estate index and Chinese macroeconomic factors during periods of economic downturn; specifically, returns on the real estate index affect the macroeconomic factors two-quarters later. We then use machine learning methods to select the most important macroeconomic factors that drive net equity value for Chinese real estate companies and forecast future equity values via Monte Carlo simulation. Finally, we estimate risk measures such as probability of default and Value-at-Risk for stylized Chinese real estate companies using the simulated net equity values, with the end goal of providing these companies with capital allocation and investment planning recommendations for asset-liability risk management.
Type of Material: Princeton University Senior Theses
Language: en
Appears in Collections:Operations Research and Financial Engineering, 2000-2023

Files in This Item:
File Description SizeFormat 
CHEN-SOPHIA-THESIS.pdf2.06 MBAdobe PDF    Request a copy

Items in Dataspace are protected by copyright, with all rights reserved, unless otherwise indicated.