I am an assistant professor of finance at the Fox School of Business at Temple University. My main research areas are asset pricing, macro-finance, financial institutions, and fintech. I received my PhD in finance from the University of North Carolina at Chapel Hill (Kenan-Flagler Business School) and a BA in economics from Cornell University. Prior to my PhD program, I worked in the Financial Stability division at the Federal Reserve Board.
Macro Financial Modeling Initiative (Becker Friedman Institute for Economics at the University of Chicago)
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We study the impact of lender competition on loan pricing using comprehensive loan-level data from the U.S. Small Business Administration (SBA) 7(a) program. Intended only for the most credit-constrained small businesses, SBA loans are originated in the banking sector and subsidized by the government through partial guarantees. In contrast to previous studies of small business lending markets, we find that greater competition is associated with lower SBA loan spreads. Further, we provide causal evidence for this relationship in a difference-in-differences analysis using bank mergers. Our results suggest that lending relationships are less important in the government-monitored-and-subsidized SBA loan market. As a result, hypothetical policies to encourage competition in the SBA loan market would benefit borrowers. Additionally, our findings support the use of product-market-specific concentration measures by regulators when evaluating bank mergers.
In the market for non-fungible tokens on the blockchain, experienced investors systematically outperform inexperienced investors. Controlling for holding period, experienced investors make 10 percentage points more per trade. NFT collections purchased by experienced investors sell out more often and more quickly in primary markets, and experience higher price growth in secondary markets. Our results suggest that NFT markets are characterized by high degrees of informational inefficiency, allowing investors with informational advantages to systematically extract profits.
Winner: Best Paper Award Junior Researcher Category at 2018 PANORisk Conference
In a model with heterogeneous banks and endogenous fire sales, the tightening of bank capital regulation can aggravate fire sales, leading to larger bank losses and higher systemic risk. When calibrated to the data, the least costly policies to mitigate systemic risk raise both ex ante capital requirements and ex post shortfall penalties. These policies also assign relatively higher capital requirements to banks that can better offset price declines during a fire sale, consistent with the recently implemented capital surcharge for global systemically important banks (G-SIBs). My findings provide further support for leading-edge macroprudential tools, including stress tests and countercyclical capital buffers.
Focusing on both micro and aggregate U.S. data, we document the existence of a significant link between aggregate uncertainty, capital markets valuations and reallocation of resources away from risky R&D-intensive capital. This link is important because a decrease in the aggregate share of R&D-oriented investments forecasts lower medium-term growth. We study a two-sector model in which one sector features relatively risky R&D-intensive capital essential to sustain growth, whereas the other sector features safer capital that is not innovation-intensive. Our model accounts for our novel empirical evidence obtained from both capital markets and aggregate data. We identify an important role for uncertainty shocks as they feature a first-order negative impact on medium-term growth and welfare.
We develop a new small open economy model (SONOMA) in which domestic corporate debt and equities are affected by shocks to both external credit and equity markets. In a novel empirical analysis of several small-but-developed economies, we show that both external debt and equity shocks are important determinants of domestic economic fluctuations, corporate leverage, and net foreign asset positions. SONOMA replicates our empirical facts about asset prices, financial flows, and economic activity.
Using the market for initial coin offerings (ICOs) as a laboratory, we provide evidence that entrepreneurs use retention to alleviate information asymmetry. The underlying technology and the absence of regulation make the ICO market well suited to study this question empirically. Using a hand-collected dataset, we show that ICO issuers that retain a larger fraction of their tokens are more successful in their funding efforts and are more likely to develop a working product. Moreover, we find that retention is a stronger signal when markets are crowded and investors do not have as much time to conduct due diligence.
The reduction in credit supply from traditional lenders following the 2007--2008 Financial Crisis contributed to a surge in direct lending and, in particular, investments by business development companies (BDCs). Using a novel hand-collected dataset, we provide the first systematic analysis of the BDC sector. We exploit three exogenous shocks to credit supply, including new banking regulations and a major finance company collapse, to establish that BDC capital acts as a substitute for traditional financing. Relying on the synthetic control method, we further document that firms' access to BDC funding has stimulated economic growth and innovation.
Using the exclusion of business development companies (BDCs) from stock indexes, this paper studies the efficacy of market discipline in the direct lending space. Amid share sell-offs by institutional investors, a drop in valuations limits the ability of affected BDCs to raise new capital and sustain their investment activity. Due to market discipline, affected BDCs reduce the risk exposure of their portfolios by shifting towards senior debt. The contraction in BDC credit hampers employment growth of their portfolio companies. The certification channel allows affected borrowers to partially offset this effect by diversifying across lenders and securing funding from new BDCs.
We document that nearly half of US public firms were eligible for the Paycheck Protection Program (PPP) in 2020, with 41.8% of those eligible choosing to borrow. Consistent with the program's objectives, borrowers tended to be smaller with less cash, higher leverage, and fewer investment opportunities. In addition, firm values declined upon PPP loan announcement and borrowers grew slower in 2020 relative to nonborrowers. We document that 13.5% of PPP borrowers, in particular those facing more public scrutiny, returned their loans after public backlash. Overall, concerns of reputational harm appeared to dissuade eligible public firms from availing emergency government funding.
We propose a method to extract the risk-neutral distribution of firm-specific stock returns using both options and credit default swaps (CDS). Options and CDS provide information about the central part and the left tail of the distribution, respectively. Together but not in isolation, options and CDS span the intermediate part of the distribution, which is driven by exposure to the risk of large but not extreme returns. Through a series of asset-pricing tests, we show that our method delivers a more accurate measure for skewness, particularly at times of heightened market stress.
We evaluate the short-horizon predictive ability of financial conditions indexes for stock returns and macroeconomic variables. We find reliable predictability only when the sample includes the 2008 financial crisis, and we argue that this result is driven by tailoring the indexes to the crisis and by nonsynchronous trading. In addition, we suggest a simple procedure for aggregating the various indexes into a single proxy for financial conditions, which can help to reduce the uncertainty faced by policymakers when monitoring financial conditions.