Zhanbing Xiao (肖战兵)

Ph.D. Student in Finance, UBC Sauder, 2017-

Research Interests:

Financial Intermediation

Corporate Finance

Political Economy

Application of Machine Learning & Fintech

Curriculum Vitae



HA 391, 2053 Main Mall, Vancouver, BC V6T 1Z2


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Working Papers

  • Agree to Disagree: Within-Syndicate Conflict and Syndicated Loan Contracting (SSRN) (Slides) 

          with Yongqiang Chu and Luca X. Lin.

Prior studies show that creditors’ simultaneous equity holding mitigates shareholder-creditor conflict. We show that a new type of conflict arises in syndicates with such dual holders, due to the heterogeneity across syndicate members’ equity-to-loan positions. We find that loans with higher within-syndicate conflicts rely less on performance covenants, which serve as tripwires to facilitate ex-post control transfer from shareholders to creditors. Renegotiation is also less likely as conflict increases. Instead, high-conflict loans rely more on capital covenants, which align shareholder-creditor interests ex-ante and incentivize shareholders to monitor. Moreover, lead arrangers retain larger shares in high-conflict loans to commit to monitoring beyond contractual provisions. Finally, high-conflict loans tend to be smaller, shorter, and more costly. 

Featured in: Duke GFMC FinReg Blog

Presented at: University of Navarra IESE Business School*;  33rd Australian Finance and Banking Conference, 2020; (* indicates by coauthors)

  • Lines of Credit, Two-Player External Liquidity (SSRN)

          with Zhongyan Zhu. 

We propose a two-player game under the pecking order framework to model credit line realization. A firm and a bank make sequential decisions, and each has two choices. Firms with sufficient internal liquidity won’t apply in the first place. Banks reject applications on concerns that borrowers can’t service drawdown interests or pay back the principal of those that submit applications. The empirical analysis focuses on both normal times and a crisis period. In normal times, credit line contracts add liquidity capacity when the cash holdings are insufficient to address unexpected cash flow shocks. In-crisis drawdowns confirm an independent demand-side story.

  • Spillover Effects of Banks' Specialization in Corporate Lending on Mortgage Lending: The Industry Expertise Channel (SSRN(Slides)

          with Yuxiang Zheng

This paper documents an industry expertise channel through which a bank's corporate lending can influence its mortgage lending. The industry expertise a bank gains through lending to firms in a specific industry strengthens its understanding of economic conditions in counties where the industry is a major sector. Thus, for households in those counties, banks can better evaluate their short-term and long-term financial conditions, and hence their mortgage affordability. Information gained from the industry expertise channel improves banks' screening and monitoring efficiencies, leading to increased allocation of mortgage credits towards counties with same industry specializations. The effects are stronger when the information asymmetry between banks and mortgage borrowers is high or when the local economies are in downturns. Mortgages originated through such a channel are also less likely to default.

Presented at: SWFA 2021 (scheduled)

  • To Sell or To Retain: Interest Rate Risk in Fixed-Rate Mortgages and Banks' Securitization  Decisions (SSRN) (Slides)

The interest rate risk embedded in 30-year fixed-rate mortgages (FRMs) leads to a decline in the value of a mortgage when the market interest rate goes up. In this paper, I show that banks with interest-insensitive liabilities are more able to absorb the interest rate risk in FRMs and therefore transfer less such risk to market investors – less mortgage securitization and more retained on the balance sheet. This is because the liabilities of such banks are similar to fixed-rate and long-term debt, thereby enabling them to tolerate losses incurred by rising interest rates. Meanwhile, holding mortgages helps these banks hedge the risk of interest rates going down. Besides, I show that mortgage refinancing in low-interest-rate periods induces prepayment risk and increases interest-insensitive banks' incentives to securitize mortgages. Furthermore, I show that interest-sensitive banks are more willing to supply refinancing mortgages to households. Last, I show that counties dominated by high-beta banks experience a much slower growth rate in house prices. Overall, my findings suggest that the interest rate risk in mortgages has important implications for banks' decisions in the mortgage market.

Selected Working in Progress

  • Do Banks’ Partisan Affiliations Shape their Lending Decisions? (Draft) (Poster

       with Isha Agarwal. 

This paper provides novel evidence on the role of banks’ partisan affiliations (independent of political pressure or rent seeking) in their lending decisions. Using county-level data on mortgage applications over the period 1994 to 2017, we find that banks’ mortgage lending is consistently larger in counties that share their political beliefs. This finding is robust to alternate definitions of political affiliations of banks and counties and controlling for observable loan characteristics and bank-year and county-year fixed effects. We find no evidence that rent extraction or political influence can explain this difference in mortgage lending. Instead, ideological differences across banks based on their partisan affiliations seem to drive the results. We show that lending decisions based on partisan allegiances have a negative effect on banks’ health as reflected in their higher non-performing loan ratios and lower return on assets.

Presented at: AFA Poster Session 2021

Older Working Papers

  • Smart Beta, "Smarter" Flows (SSRN)

       with Jie CaoJason Hsu, and Xintong Zhan. 

We examine the impact of smart beta equity exchange-traded funds (ETFs) on how investors evaluate active mutual fund performance. We find that when smart beta ETFs are actively traded, mutual fund flows become “smarter”, with a higher sensitivity to alphas from multi-factor models.

AwardsETF Research Academy Award of the Paris-Dauphine House of Finance (in association with Lyxor Asset Management), 2018. Chicago Quantitative Alliance (CQA) Academic Competition Award, Chicago, 2017. Chicago Quantitative Alliance Asia (CQAsia) Academic Award, Hong Kong, 2016.

Presented at:  Annual CQAsia Conference (2016)*, 11th Annual NUS-Risk Management Conference (2017)*, CICF (2017)*, The Role of Hedge Funds and other Collective Investment Funds in the Modern World (2017)*, McGill World Symposium on Investment Research (2018)*, NFA (2018)* (* indicates by coauthors)


  • A New Lease on Firm Behavior (Matteo Binfare, Robert A. Connolly, Fotis Grigoris and Crocker H. Liu) , AFBC 2020