Marco Di Maggio

Marco Di Maggio

Ogunlesi Family Associate Professor of Business Administration

Ogunlesi Family Associate Professor of Business Administration

Finance
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Marco Di Maggio
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Marco Di Maggio is a faculty member in the Finance Unit and a faculty research fellow at the National Bureau of Economic Research. Before joining HBS, he was a faculty member in the finance and economics division of Columbia Business School.

Professor Di Maggio has recently developed the first HBS course on FinTech tailored to MBA students. In 2019 Professor Di Maggio developed a new Executive Education Program on Fintech (https://www.exed.hbs.edu/leveraging-fintech-innovation-grow-compete/) together with Luis Viceira and David Scharfstein. This program is ideal for rising executives in a broad array of financial institutions, from banks to asset management firms, as well as for individuals who are planning to launch new enterprises aimed at disrupting key areas of financial markets (For questions, please contact executive_education@hbs.edu).  

Professor Di Maggio’s current research focuses on financial intermediation with a particular focus on how new technologies have disrupted financial markets and its effects on firms and individuals. His work has been published in leading academic peer-reviewed journals such as the American Economic Review, Journal of Finance, Journal of Financial Economics, The Review of Financial Studies, Management Science and has been widely cited by outlets such as the Wall Street Journal, The Economist, Bloomberg, Institutional Investor, Slate and Forbes.

In 2016, Poets and Quants named him to its list of the Best 40 Under 40 Business School Professors. 

Featured Work
Buy Now, Pay Later Credit: User Characteristics and Effects on Spending Patterns
Firms offering "buy now, pay later" (BNPL) point-of-sale loans with minimal underwriting have grown in popularity in the last couple of years. According to Worldpay, BNPL accounted for 2.1% – or roughly $97b – of global e-commerce transactions in 2020, and is expected to double to 4.2% by 2024. 
We are the first to provide a detailed look into the US BNPL market by constructing a large panel of BNPL users from transaction-level data. BNPL access increases both total spending levels and the retail share in total spending, ultimately, facilitating consumption smoothing.
Invisible Primes: Fintech Lending with Alternative Data
A key policy question raised by the advent of fintech lenders revolves around the impact on credit availability of credit models that employ alternative data and algorithmic underwriting. We exploit anonymized administrative data provided by a major fintech platform (Upstart Inc.) to investigate whether using alternative data to assess borrowers' creditworthiness results in broader credit access. Comparing actual outcomes of the fintech platform’s model to counterfactual outcomes based on a “traditional model” used for regulatory reporting purposes, we find that about 25% of the applications with low credit scores would have been denied if not for Upstart's underwriting model. We further find that the mismatch between the traditional and Upstart model is magnified among low-credit score borrowers. This finding highlights the potentially uneven consequences of using alternative data: those who benefit are those who are most in need.
Fintech Borrowers: Lax-Screening or Cream-Skimming?

Financial markets have recently witnessed a disruptive force: the rise of online intermediaries and, more generally, fintech companies, i.e., firms that apply technology to improve financial activities. Fintech companies have targeted the consumer credit market, which is one of the largest credit market, with outstanding credit of $3.8 trillion. We show two key results. First, while fintech companies target consumers with higher FICO score, fintech borrowers are more likely to default ex post. This result is due to borrowers using the fintech loan to fund additional expenses rather than to consolidate their existing debts, which leads them to be overextended. Second, in contrast to the narrative that fintech use alternative data, we find that fintech companies tend to focus on the hard information contained in the credit reports, more so than traditional banks. In the same spirit as regulators introduced the "ability to repay" rules for mortgage products in the aftermath of the subprime crisis, regulators might be need to more closely monitor the borrowers' ability to service their unsecured debt and the way these additional funds are actually used by the borrowers.

Second Chance: Life Without Student Debt
Rising student debt is considered one of the creeping threats of our time. This paper examines the effect of student debt relief on individual credit and labor market outcomes. We find that borrowers experiencing debt relief reduce their indebtedness by 26%, by both reducing their demand for credit and limiting the use of existing credit accounts, and are 12% less likely to default on other accounts. After the discharge, the borrowers' geographical mobility increases, as well as, their probability to change jobs and ultimately their income increases by more than $4000, which is equivalent to about two months' salary. These findings speak to the benefits of intervening in the student loan market to reduce the consequences of debt overhang problems by forgiving student debts.    
Brokers and Order Flow Leakage: Evidence from Fire Sales

Using trade-level data, we study whether brokers play a role in spreading order flow information. We focus on large portfolio liquidations, which result in temporary drops in stock prices, and identify the brokers that intermediate these trades. We show that these brokers’ best clients tend to predate on the liquidating funds: at the beginning of the fire sale, they sell their holdings in the liquidated stocks, to then cover their positions once asset prices start recovering. The predatory trades generate at least 50 basis points over ten days and cause the liquidation costs for the distressed fund to almost double. These results suggest a role of brokers in fostering predatory behavior and raise a red flag for regulators. Moreover, our findings highlight the trade-off between slow execution and potential information leakage in the decision of optimal trading speed.


The Relevance of Broker Networks for Information Diffusion in the Stock Market
This paper shows that the network of relationships between brokers and institutional investors shapes the information diffusion in the stock market. We exploit trade-level data to show that trades channeled through central brokers earn significantly positive abnormal returns. We find that a key driver of these excess returns is the information that central brokers gather by executing informed trades, which is then leaked to their best clients. Brokers share information about one client's trades with other clients, who then profit by copying those trades. The best clients of the broker executing the informed trade, and the asset managers affiliated with the broker, are among the first to benefit from the information about order flow. This evidence also suggests that an important source of alpha for fund managers is the access to better connections rather than superior skill.
How Quantitative Easing Works: Evidence on the Refinancing Channel

When LSAPs are needed the most, simply bending the yield curve through purchasing government debt is not effective for stimulating the mortgage market (a key sector of the economy for the transmission of monetary policy). Purchasing mortgage-backed securities when banks are reluctant to lend can very effectively open a direct-lending channel from central-bank purchases to households. Given the limited spillover of Fed purchases during times of stress, Federal Reserve Act provisions that restrict Fed purchases to government-guaranteed debt have important consequences in allocating credit to certain sectors (i.e., housing) and particular segments within those sectors (i.e., conforming mortgages). 

The Unintended Consequences of the Zero Lower Bound Policy

Our novel evidence suggests that in the times of unusually low interest rates money market fund managers increased, on average, their portfolios’ risk. We also show that funds that were not successful in retaining their investors’ base, or were worried about negative reputation spillovers, were more likely to exit. Our results further suggest that the zero lower bound policy triggered a reduction in capital supply to financial and large corporate sectors and increased the financial markets’ exposure to costly runs and defaults.

The Value of Trading Relationships in Turbulent Times
Our recent work investigates dealers' trading behavior and pricing strategy in the corporate bond market to shed new light on the role of the network of existing relationships among dealers in shaping the transmission of risk and influencing market liquidity. We show that trading relationships may sometimes act as a buffer in periods of distress, but they might also accentuate systemic fragility, as connections with vulnerable dealers might affect trading outcomes even for sound dealers. Finally, we find evidence that dealers drastically reduced their inventory during the financial crisis. These results can help inform the debate on the risks posed by the interconnectedness of the financial system, showing how this could be a source of market fragility and illiquidity.
Journal Articles
Working Papers
Cases and Teaching Materials
Awards & Honors
Winner of the 2021 Dimensional Fund Advisors Prize for Distinguished Paper in The Journal of Finance for “Stock Market Returns and Consumption” (December 2020) with Amir Kermani and Kaveh Majlesi.
Winner of the 2020 Case Centre Award in the Finance, Accounting and Control category for “Snap Inc's IPO (A)” (HBS Case 218-006).
Winner of the 2018 AQR Asset Management Institute Young Researcher Award.
Winner of the 2018 RFS Rising Scholar Award from The Review of Financial Studies for his paper with Amir Kermani, "Credit-Induced Boom and Bust" (November 2017).
Included as one of “40 Best Business School Professors Under 40” by Poets & Quants in 2016.
Winner of the 2016 Best Paper in Market Microstructure Award for “The Value of Trading Relationships in Turbulent Times” with Zhaogang Song and Amir Kermani (forthcoming in the Journal of Financial Economics). The award was sponsored by NASDAQ at the Annual Meeting of the Financial Management Association.
Received an INQUIRE Europe Research Grant in 2016.
Received an NBER Household Finance Working Group Grant from the National Bureau of Economic Research in 2016.
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