Financial Engineering

The government budget constraint ties the market value of government debt to the expected present discounted value of fiscal surpluses. We find evidence that U.S. Treasury investors fail to impose this no‐arbitrage restriction in the United States. Both cyclical and long‐run dynamics of tax revenues and government spending make the surplus claim risky. In a realistic asset pricing model, this risk in surpluses creates a large gap between the market value of debt and its fundamental value, the PDV of surpluses, suggesting that U.S. Treasuries may be overpriced.

How should an investor value financial data? The answer is complicated because it depends on the characteristics of all investors. We develop a sufficient statistics approach that uses equilibrium asset return moments to summarize all relevant information
about others’ characteristics. It can value data that is public or private, about one or many assets, relevant for dividends or for sentiment. While different data types, of course, have different valuations, heterogeneous investors also value the same data

This paper theoretically and empirically investigates the effects of liquidity regulation on the banking system. We document that the current quantity-based liquidity rule has reduced banks’ liquidity risks. However, the mandated liquidity buffer appears to crowd out bank lending and lead to a migration of liquidity risks to banks that are not subject to liquidity regulation. These findings motivate a model of liquidity regulation with endogenous liquidity premiums and heterogeneous banks.

How can we measure the extent to which data-intensive firms are using their market power? Economists typically look to markups as evidence of market power. Using a simple model with firms that price risk in their capital allocation and production decisions, we highlight the competing forces that make markups an unreliable measure of data-derived market power. Instead, we show how markups measured at different levels of aggregation reflect data and distinguish data from other intangible investments.

We develop a novel technique to extract credit-relevant information from the text of quarterly earnings calls. This information is not spanned by fundamental or market variables and forecasts future credit spread changes. One reason for such forecastability is that our text-based measure predicts future credit spread risk and firm profitability. More firm- and call-level complexity increase the forecasting power of our measure for spread changes. Out-of-sample portfolio tests show the information in our measure is valuable for investors.

We investigate banks' benefits and costs of having access to LOLR. Integrating novel data sets we estimate the borrowing capacities of euro area banks at the ECB. Controlling for ratings, we find that banks with more fragile funding are likely to borrow more from the ECB during the great financial and euro area sovereign debt crises. We develop a dynamic model of a bank and calibrate it to our empirical estimates. A bank with access to LOLR has higher equity value and makes larger investments in new loans, but it is more leveraged, pays more dividends and issues less equity.

After the global financial crisis, the yields of U.S. Treasury bills frequently exceed other risk-free rate benchmarks, thereby pointing to a diminishing convenience premium. Constructing a new measure of dealers’ balance sheet constraints for providing intermediation in U.S. Treasury markets, we trace these diminishing convenience premiums to primary dealers’ ability to act as intermediaries.