Professor Jing Wu is an assistant professor at the Department of Decision Sciences and Managerial Economics of CUHK Business School, the Chinese University of Hong Kong, an executive committee member of the Hong Kong-Shenzhen Finance Research Center, and a senior scientist at the Laboratory for AI-Powered Financial Technologies. He receives his Ph.D. (major in operations management, minor in economics & finance) and MBA from the University of Chicago Booth School of Business and his bachelor's degree in Electronic Engineering from Tsinghua University.
Professor Wu's primary research fields are the operations-finance interface, global supply chains, economic networks, and big data applications. His papers appears in journals such as Management Science, M&SOM, and POMS. Professor Wu contributes to the industry by advising a Hong Kong FinTech firm and an asset management firm in Mainland China. Prior to Greater China, he worked at Deutsche Bank, New York as a quantitative strategist.
Professor Jing Wu
Decision Sciences and Managerial Economics, CUHK Business School, the Chinese University of Hong Kong
The Hong Kong-Shenzhen Finance Research Center, the Shenzhen Finance Institute (SFI)
+852 3943 5299
Rm 915, 9/F Cheng Yu Tung Building, Shatin, Hong Kong SAR, China
We study if global supply chain relationships help firms access cross-border financing in formal international financial markets. Comparing two firms that are otherwise similar in covariates and pre-formation outcomes through a difference-in-differences strategy with matching, we find the formation of global supply chain relationships to be associated with a sustained increase in accessing of cross-border financing, across all major formal financing venues including cross-listings, bonds, syndicated loans, and M&As. Instrumenting global supply chain formation using reduction in physical trade costs yields similar results. This finding is also robust to controlling for strategic disclosure concerns. The estimated effect is stronger for firms in environments with higher accounting and ethical standards and small and growing firms, but weaker for firms in countries with tighter capital controls and more volatile exchange rates. This suggests global supply chain formation helps cross-border financing more through information production, not cash flow relocation or re-denomination.
I'm a paragraph. Click here to add your own text and edit me. It’s easy. Just click “Edit Text” or double click me to add your own content and make changes to the font. I’m a great place for you to tell a story and let your users know a little more about you.
with Michael Hertzel, Jie Peng and Yu Zhang, in Revision.
(Featured at 2019 MSOM SIG, 2019 Wharton EMPOM)
This paper provides evidence that the formation of global supply chain partnerships increases access to cross-border financing. The findings are detected in all three major financing markets - equities, syndicated loans, and public debt. Difference-in-differences and instrumental variable tests allow us to draw causal inferences from our results. We propose that our findings reflect the factor of informational visibility where less visible firms can overcome informational obstacles to cross-border financing by establishing global supply chains. Specifically, we provide evidence that firms that are small, held less by institutional investors, and followed by fewer analysts have more benefit in cross-border financing from the formation of the global supply chain. Our findings have important implications for firms attempting to integrate into the global supply-chain network. More broadly, our findings suggest that the information generated by operational activities can have important effects on subsequent financing activities.
with Vernon Hsu, 2nd round review at Management Science.
(Featured at 2019 CSAMSE Best Paper Award)
Classical inventory theory suggests that inventory plays a vital role in matching demand and supply. This paper provides both macro and micro evidence that inventory can be used as a financial instrument to take advantage of arbitrage opportunities in financial markets with limited capital mobility. Using data from China’s country-level metal commodity imports and firm-level inventory from metal processing industries (with metal commodities as primary inputs), we show that firms can utilize the inventory of an imported product to carry lower-cost capital into a country with strict capital controls and thus gain higher financial returns. Specifically, at the country-level, we show that levels of imported metal commodities are positively associated with the expected returns from financial arbitrage. At the firm-level, we find that a higher expected return from financial arbitrage will incentivize a firm to increase its inventory level through increased short- term borrowing. In addition, firms with higher borrowing capacity, larger size, or higher sales growth are more active in using inventory as an instrument to seek higher financial gains. We also utilize a unique regulatory policy shock as a natural experiment to establish causality in our empirical analysis.
(Featured at 2021 CSAMSE Best Paper Award, 2021 MSOM)
Perception regarding a focal firm's corporate social responsibility (CSR) depends not only on itself but also on its known suppliers. This paper provides the first empirical evidence linking CSR and supply chain information disclosure together. Specifically, it uncovers robust evidence that firms greenwash their CSR image via voluntarily disclosing environmentally responsible suppliers while concealing "bad" ones. Exogenous variations in abnormal temperatures around the world drive variations in the selective disclosure of "good" suppliers, supporting a causal interpretation of our finding. Supply chain greenwashing is more prevalent for firms who face higher competition, care more about their brand awareness, and for firms that are more profit-driven and held more by institutional investors. The greenwashing behavior mitigates after implementing mandatory CSR disclosure policies. Finally, firms who greenwash supply chains observe both sales and profitability increase, but only for the short-term.
(Featured at 2020 ADBI PRN Joint Conference, 2021 MSOM SIG)
The uncertainty around trade and foreign economic policy contributes to supply chain risk. Whether such policy uncertainty will bring some production back to the U.S. or only a redistribution of the global supply chains is theoretically ambiguous and warrants an empirical analysis. We study the impact of trade and foreign economic policy uncertainty on the supply chain networks of American firms. We use firm-level global supply chain data, transaction-level shipping container data, and policy uncertainty indexes constructed from leading media outlets to study how policy uncertainty is associated with changes in supply chain networks. When U.S. trade policy uncertainty rises, firms with majority domestic sales decrease their supplier base abroad, while firms with majority foreign sales increase the number of foreign suppliers. Firms also substitute among foreign countries in response to their respective economic policy uncertainty – shifting suppliers from countries with higher uncertainty to ones with lower uncertainty. Firms that require more specific inputs, produce more differentiated products, have higher market shares, and are located in a more central position in the production network are more sensitive to policy uncertainty. In response to policy uncertainty, the supply chain restructuring puts the market value at risk. Our heterogeneous findings suggest that firms react differently to operational risk due to changing economic policies, as managers should consider their customers’ locations when making global supply chain restructuring decisions.
5. "Credit Risk Propagation along Supply Chains: Evidence from the CDS Market,"with Senay Agca, Volodymyr Babich, and John R. Birge, Management Science, forthcoming, media at ChicagoBoothReview.
7. "Sourcing from Suppliers with Financial Constraints and Performance Risk,” with Christopher S. Tang and S. Alex Yang, M&SOM, Vol. 20, No. 1, 2018, p. 70-84, media at Forbes.
8. "Credit Rating Prediction Through Supply Chains: A Machine Learning Approach,” with Zhaocheng Zhang and Sean Zhou, POMS, forthcoming.
9. "Doing Business with Friends versus Making Friends in Business,” with Haoyuan Ding, Yichuan Hu, Han Jiang, and Yu Zhang, 2nd round review at Management Science.
11. "The Impact of COVID-19 on Supply Chain Credit Risk," with Senay Agca, John R. Birge, and Zi'ang Wang, in revision, media at CUHK, SMU, Reuters, 观察者网.
12. "The Bullwhip Effect in Servicized Manafacturers,” with Yimeng Niu, Shenyang Jiang, and Zhibin Jiang, submitted to Management Science.
FINA6020 FinTech Analytics (2019-2021, CUHK)
DSME6682 FinTech Application (2019-2021, CUHK)
MS6325 Operations Management (2016-2019, CityU)
Supply Chain Finance (2017, Tsinghua EMBA)
DSME6756 Business Intelligence Techniques and Applications (2019-2020, CUHK)
FB8918 Machine Learning for Business Research (2018-2019, , CityU Ph.D. Elective)
Project 1. UBS (Hong Kong) 2017.09-2017.12
We investigate the optimal trading execution strategy of in the China A-Share market by different investment styles and market liquidity conditions. The research outcome is featured at the Annual UBS APAC Quant Conference.
Project 2. A Top Investment Bank 2019.06-current
We develop the credit risk model for small & middle enterprises based on their financial information and their economic networks.
FOR RESEARCH STUDENTS:
We always welcome undergraduate and graduate research students. Our RAs are accepted in top business/economic Ph.D. programs. Email me for a research opportunity.
FOR QUANT SOLUTIONS:
We partner with institutional research teams at Deutsche Bank, JP Morgan, and UBS. Our research has practical implications for quantitative investing and beyond. Email me for related industry opportunity.