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Posts
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publications
Impact of the Opening of Shanghai Free Trade Area on the Port Economy in Hong Kong
Published in China Circulation Economy, 2017
Investigated the impact of the Shanghai Free Trade Area (FTA) on Hong Kong’s port economy using a Difference-in-Differences (DID) approach and border analysis. The analysis revealed a crowding-out effect of the Shanghai FTA on Hong Kong’s import-export market, attributed to Hong Kong’s dependence on sales and import volume rather than production innovation and R&D capabilities.
Recommended citation: G. Sun. Impact of the Opening of Shanghai Free Trade Area on the Port Economy in Hong Kong China, Circulation Economy, 2017
Carry Trade and the Theoretical Framework of “Impossible Trinity” Theory: An Empirical Analysis Based on TVP-SV-VAR
Published in Finance Forum, 2022
This paper evaluated China’s capital account liberalization and exchange rate marketization by integrating carry trade into the Impossible Trinity framework. Built a theoretical model and using TVP-SV-VAR analysis to examine the short- and long-term impulse responses between carry trade, capital controls, exchange rate stability, and monetary policy independence. Findings revealed that carry trade significantly impacts the independence of monetary policy, supporting a phased approach to capital account liberalization, starting with Portfolio Investment, followed by Financial Derivatives and FDI accounts.
Recommended citation: 郭桂霞,and 孙歌悦."人民币套息交易与“三元悖论”理论框架——基于TVP-VAR模型的实证研究." 金融论坛 27.11(2022):10-20. doi:10.16529/j.cnki.11-4613/f.2022.11.003.
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Bypassing Capital Interventions: Carry Trades via Commodity Futures Market
Published in 2024 Southern Economics Association (SEA) 94th Annual Meeting, 2024
Advisor: Prof. Tomas Williams
This project investigates commodity carry trade in developing countries, testing two key hypotheses: 1. Commodity liquidity risk reduces carry trade returns (impact: -0.226) 2. Capital controls amplify the negative impact of liquidity risk
A Staggered-DID model is employed using 4,000 daily capital intervention events from the Global Trade Alert (GTA) dataset. A Large Language Model (LLM) extracts regional information from 25,035 commodity contracts (Refinitiv), which is merged with Bloomberg’s carry trade returns to analyze liquidity risk’s effect on returns. The project’s findings were presented at the 2024 SEA Annual Meeting, offering new insights into the commodity-carry trade market equilibrium.
Recommended citation: G. Sun. (2024). "Bypassing Capital Interventions: Carry Trades via Commodity Futures Market." 2024 Southern Economics Association (SEA) 94th Annual Meeting.
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talks
Bypassing Capital Interventions: Carry Trades via Commodity Futures Market
Published:
Advisor: Prof. Tomas Williams
- Conducted empirical research on commodity carry trade in developing countries, testing two key hypotheses:
- Commodity liquidity risk significantly reduces carry trade returns (estimated impact: -0.226).
- The negative impact of liquidity risk is amplified by capital controls.
- Utilized a Staggered-DID model to investigate bypass mechanisms in response to diverse capital control policies. The analysis was based on daily capital intervention data (4,000 events) from the Global Trade Alert (GTA) dataset.
- Built a Large Language Model (LLM) to extract regional information from 25,035 commodity contracts in the Refinitiv dataset. Merged this with Bloomberg’s daily carry trade returns to assess the influence of liquidity risk on carry trade returns and develop a quantitative model for the commodity-carry trade market equilibrium.
- Presented at the 2024 Southern Economics Association (SEA) 94th Annual Meeting on November 2024.
Recommended citation: Sun, Geyue, Bypassing Capital Interventions: Carry Trades via Commodity Futures Market (December 30, 2024).
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Daily Capital Control Index: Powered by Machine Learning
Joint work with: Prof. Roberto Samaniego This project focuses on the development of a high-frequency Daily Capital Control Index for 119 countries, spanning from January 1, 2000, to the present. The index tracks six categories of capital account interventions, offering a real-time tool for the tracking and analysis of global capital control policies. By providing timely and granular insights, the index serves as a critical resource for researchers, policymakers, and market participants seeking to understand cross-country differences in capital control measures. To ensure precision, the index employs machine learning techniques, including Linear Regression and LASSO, trained on the Ka-open Index from the IMF’s Annual Report on Exchange Arrangements and Exchange Restrictions (AREAER). The project also includes the development of a comprehensive dataset and a user-friendly website that enables real-time updates and dynamic access to the dataset, facilitating seamless access to up-to-date capital control information.
teaching
Instructor
ECON1011 Principle of Macroeconomics, George Washington University, 2022
- Delivered lectures independently: Taught four days per week during the summer session, with 90-minute classes each day, effectively managing course content and student engagement.
- Created the syllabus and learning materials: Developed a comprehensive syllabus, prepared engaging learning materials, and conducted exams to provide a well-structured and complete learning experience.
- Achieved a 100% student satisfaction rate: Students praised the clarity and engagement of lectures, as well as the effectiveness of the learning materials and the support provided throughout the session.
Teaching Assistant
ECON 8305 Macroeconomics I (PhD Level), George Washington University, 2022
Teaching Assistant
ECON 8306 Macroeconomics II (PhD Level), George Washington University, 2023