Research Interest

My research is mainly focused on corporate finance and banking. Particularly, my research studies lines of credit (a flexible loan) from the demand side (corporation) and the supply side (bank) and how credit lines are related to corporate credit risk, liquidity risk, banks' funding risk, XVA, and central bank's monetary policies. Recently, I study how credit lines can mitigate climate risk.

My studies also focus on interdisciplinary topic, such as the combination of signal processing and asset pricing.

Conferences

The 4th Frontiers of Factor Investing, Lancaster University Management School.

European Financial Management Association (EFMA) 2024 Annual Meeting.

Working Papers

Quantitative Easing, Banks' Debt Overhang Costs, and Credit Line Prices (With Mario Cerrato, job market paper, accepted by conferences)

Abstract: Recently, Cooperman et al. (2023) show that the covariance of banks’ funding costs and credit lines draw-downs is debt overhang costs for the bank’s equity holders. In this paper, we empirically and theoretically study whether this cost can be mitigated by central banks’ quantitative easing. We focus on the COVID-19 shock. Based on Cooperman et al. (2023), we empirically find that funding costs generate frictions related to banks’ shareholders (debt overhang cost), and banks transfer that cost to the credit lines’ fees. However, our econometric analysis, event studies, and theory suggest and formalise why central banks’ quantitative easing (QE) can be crucial to mitigating that cost, thereby ensuring a cheaper supply of credit to the economy. Our findings shed further light on the intricate relationship between banks’ funding costs and related debt overhang (Andersen et al. 2019), focusing on an important source of credit for firms: credit lines.

European firms, Panic Borrowing and Credit Lines Drawdowns: What did we learn from the COVID-19 Shock? (With Mario Cerrato and Hormoz Ramian, online appendix, submitted manuscript)

Abstract: Using data for European firms and COVID-19 as an exogenous shock, we show that at the peak of the COVID-19 shock in 2020:Q2, European firms went into a "panic borrowing'' status and drew down  €87bn in a very short period. This aligns with what was reported in early studies for US firms (Acharya & Steffen 2020b). More interestingly, we explore the heterogeneity across European countries and industries and the interplay between banks (supply of credit lines) and firms. We report some new and interesting results. First, heterogeneity across countries and industrial exposure to the COVID-19 shock help us understand why some firms drew down credit lines in March 2020. Banks accommodated the demand for credit insurance during the same period. Our study exploits the implications of social distancing policies on corporate operations across Europe. The novel aspect of our study is that, unlike the previous literature, we focus on shocks unrelated to firms' fundamentals.

The Dark Side of FX Volume: Evidence from Large Dealer Banks (With Mario Cerrato and Tongtong Want, working paper)

Abstract: We employ two novel proprietary fx volume and order flows data-sets and provide evidence on the informative role of fx volume before and after 2008. Our empirical evidence suggests that US$ spot fx trading volume post-2008, is highly associated with the scrambling for US dollars discussed in Bianchi et al (2021). In short, FX dealers, hit by an adverse shock on capital, reduce the intermediation (supply) of US dollar and increase that of the risky asset (foreign currency) by skewing the foreign quote to attract US dollars. We present evidence suggesting that one possible mechanism behind this effect is related to dealers' balance sheet frictions. In this paper we focus on debt overhang cost (Myres (1974)). We show that debt overhang cost introduces a shadow cost on capital for the dealer and this cost could explain why she has an incentive to increase the intermediation of foreign currency and reduce that of US dollars. We propose and discuss a theoretical model to motivate it. 

Firm-Oriented Credit Line Model

Abstract: Literature focuses on lenders’ determinants in credit line issuance, but little work mentions why borrowers choose this debt financing tool. We develop a corporate financing and investment model and explore the optimal operation decision for demanding credit lines. Our model highlights the solvency risk in firms’ credit line usage and provides rationales for firms drawing credit lines for cash savings in aggregate shocks. Using European data during the COVID-19 crisis, we provide stylized facts about credit line usage, pandemic exposure, and corporate productivity. 

The Time Function of Stock Price: An integral white noise model and its time- and frequency- domain characteristics (With Hong Gao)

Abstract: This paper defines the quantitative relationship between the stock price and time as a time function. Based on the empirical evidence that “the log-return of a stock is the series of white noise”, a mathematical model of the integral white noise is established to describe the phenomenon of stock price movement. A deductive approach is used to derive the auto-correlation function, displacement formula and power spectral density (PSD) of the stock price movement, which reveals not only the characteristics and rules of the movement but also the predictability of the stock price. The deductive fundamental is provided for the price analysis, prediction and risk management of portfolio investment.