Financial Engineering

The use of order flow information by financial firms has come to the forefront of the regulatory debate. A central question is: Should a dealer who acquires information by taking client orders be allowed to use or share that information? We explore how information sharing affects dealers, clients and issuer revenues in U.S. Treasury auctions. Because one cannot observe alternative information regimes, we build a model, calibrate it to auction results data, and use it to quantify counter-factuals. The model's key force is that sharing information reduces uncertainty about future value.

We study how investors' preferences for robustness influence corporate investment, financing, and compensation decisions and valuation in a financial contracting model with agency. We characterize the robust contract and show that early liquidation can be optimal when investors are sufficiently ambiguity averse. We implement the robust contract by debt, equity, cash, and a financial derivative asset. The derivative is used to hedge against the investors' concern that the entrepreneur may be overly optimistic.

This paper estimates a structural model of unconventional monetary policy transmission through bank balance sheets using cross-sectional instruments for loan and deposit demand. We estimate the demand for banking at a branch-specific level from the response of a bank's quantities at one branch to interest rate changes caused by demand shocks at other branches. Depositors are considerably less sensitive to interest rates than corporate or mortgage borrowers.

"Big data" financial technology raises concerns about market inefficiency. A common concern is that the technology might induce traders to extract others' information, rather than to produce information themselves. We allow agents to choose how much they learn about future asset values or about others' demands, and we explore how improvements in data processing shape these information choices, trading strategies and market outcomes. Our main insight is that unbiased technological change can explain a market-wide shift in data collection and trading strategies.

This paper shows that when the bankruptcy code protects the creditors' rights with no impairments to secured creditors, issuance of debt such as repo with exemption from automatic stay adds no value. When the bankruptcy process admits violations of absolute priority rules or results in collateral impairments to secured creditors, the liability structure includes short-term debt, with safe harbor protection when the pledged collateral satisfies a minimum liquidity threshold.

Many financial markets are operated as electronic limit order books (LOBs). Over short time scales, seconds to minutes, LOBs can be best understood and modeled as stochastic dynamical systems, and, specifically, ones that exhibit interesting and relevant queueing phenomena. I will offer a brief overview of algorithmic trading in a limit order book, and highlight how queueing phenomena play an important role in trade execution, and as a consequence in market behavior.

Koszegi and Rabin (2006, 2007) develop a model of expectations-based reference-dependent preferences, in which the agent experiences prospect-theory inspired "gain-loss utility" by comparing his actual consumption to all his previously expected consumption outcomes. Koszegi and Rabin (2009) generalize the static model to a dynamic setting by assuming that the agent experiences both contemporaneous gain-loss utility over present consumption and prospective gain-loss utility over changes in expectations about future consumption.

Over the past decade, data has transformed everyday life. While it has changed the way people shop and businesses operate (Goldfarb and Tucker, 2019), it has only just begun to permeate economists thinking about the aggregate economy. In the early twentieth century, economists like Schultz (1943) analyzed agrarian economies and land-use issues. As agricultural productivity improved, production shifted more to manufacturing. Modern macroeconomics adapted with models featuring capital and labor, markets for goods, and equilibrium wages (Solow, 1956).

We estimate the benefit of life-extending medical treatments to life insurance companies. Our main insight is that life insurance companies have a direct benefit from such treatments as they lower the insurer's liabilities by pushing the death benefit further into the future and raise future premium income. We apply this insight to immunotherapy, treatments associated with durable gains in survival rates for a growing number of cancer patients. We estimate that the life insurance sector's aggregate benefit from FDA approved immunotherapies is $9.8 billion a year.