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, and an executive committee member of the Hong Kong-Shenzhen Finance Research Center. 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 work appears in journals such as Management Science and M&SOM. 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.
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with Senay Agca, Volodymyr Babich, and John R. Birge, major revision at Management Science, media at ChicagoBoothReview.
(Featured at 2018 SFS Cavalcade, 2018 NFA, 2018 EEA)
We find that credit risk propagates through multiple supply chain tiers for both positive and negative credit shocks. Specifically, rating and industry-adjusted CDS spreads change by 44-71 bps for the first tier. Strong propagation persists for 2nd and 3rd tiers for adverse shocks but attenuates for favorable shocks. Such effects are not observed for inactive supply chain links. Credit risk propagation is magnified with longer-term supply-chain relations, trade credit, differentiated products, and leverage, but is moderated with investment grade rating and high inventory. Credit risk propagation is stronger for supply chain partners followed by the same analysts.
with Michael Hertzel, Jie Peng and Yu Zhang, R&R at Management Science.
(Featured at 2019 MSOM SIG, 2019 Wharton EMPOM)
We study if global supply chain relationships help firms access cross-border financing in formal international financial markets, using a comprehensive dataset of global supply chain relationships and cross-border financing deals. Comparing two firms that are otherwise similar in covariates and pre-formation outcomes through a difference-in-differences strategy with matching, we find that formation of global supply chain links is positively associated with a sustained increase in cross-border financing across bond, cross-listing, syndicated loans and M&A markets. This association is robust to controlling for standard firm-level determinants, industry-specific and country-specific shocks, and endogeneity. We examine multiple economic channels. We establish an important informational channel for the relation between global supply chain integration and cross-border financing, supported by a battery of tests, including heterogeneity, regression discontinuity, and supply chain voluntary disclosure. We do not find capital control, currency risks, or external financing dependence to be as important.
with Yilin Shi and Yu Zhang.
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.
with Vernon Hsu, major revision 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 2020 ADBI PRN Joint Conference)
We study the impact of trade and other economic policy uncertainty on supply chain networks of American firms. The uncertainty around the trade and other economic policy contributes to supply chain risk. Whether such policy uncertainty will bring production back to the U.S. or only a redistribution of the global supply chains is theoretically ambiguous and warrants an empirical analysis. Using firm-level global supply chain data, transaction-level shipping container data, and policy uncertainty indexes, we investigate the question using reduced-form empirical specification with high dimensional fixed effects. Rather than inducing production to come “home”, on average higher U.S. trade policy uncertainty predicts an increase in foreign supplier relationships, driven by firms with majority foreign sales. In contrast, those with mostly domestic sales mildly decrease foreign supplier relationships. American firms also appear to substitute among foreign countries in response to foreign-country-specific economic policy uncertainty – shifting suppliers from countries with higher uncertainty to ones with lower uncertainty. Firms with more bargaining power respond more to all measures of economic policy uncertainty. Corporate managers should take their customers’ locations into account when making sourcing decisions; in particular, reducing operational risk due to changing economic policies may involve additional offshoring rather than re-shoring.
6. "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.
with Nikolay Osadchiy and William Schmidt, Management Science, forthcoming.
8. "Credit Risk Prediction Through Supply Chains: A FinTech Application,” with Zhaocheng Zhang and Sean Zhou, submitted, draft available upon request.
9. "CEO Myopia and Supply Chain Investment,” with Yifan Jia, Zheng Wang, and Zilong Zhang, in revision.
10. "Trade Credit Late Payment and Industry Structure,” with John R. Birge and Hsiao-Hui Lee, submitted.
11. "Supply Chain Network Structure and Firm Returns,” with John R. Birge.
12. "Spillover Effects of Credit Default Swaps on Corporate Disclosure along the Supply Chain,” with Matthew Cedergren, Ting Luo, and Yue Zhang, submitted
13. "The Impact of COVID-19 on Supply Chain Credit Risk," with Senay Agca, John R. Birge, and Zi'ang Wang, submitted, media at CUHK, SMU, Reuters, 观察者网.
FINA6020 FinTech Analytics (2019-2020, CUHK)
DSME6682 FinTech Application (2019-2020, 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.