Financial Engineering

Top marketers today don't shy away from financial accountability. In fact, they actively hold themselves and their organizations to account for the return on marketing investments because they believe marketing makes a big difference in building the business. That commitment plays out in many ways, from  more effective campaigns to more satisfied customers; from more profitable promotions, to higher returns to shareholders.

We wrote this book to address the most pressing marketing performance questions for CMOs who have an investor's mindset.

In the presence of aggregate risk, governments face a trade-off between insuring taxpayers or bondholders. The literature assumes that the government can finance deficits at the risk-free rate, protecting bondholders at the expense of taxpayers. We characterize the implications of this assumption on the surplus process. Under reasonable debt dynamics, counter-cyclical debt issuance that protects taxpayers against adverse macro-economic shocks is limited in time and scope, and comes at the expense of higher long-run risk.

We use topic modeling to construct novel news-based measures for tracking energy markets. Our parsimonious yet comprehensive set of indicators summarizes the information content of millions of news articles and forecasts oil spot, futures, and energy company stock returns, and changes in oil volatility, production, and inventories. Using an econometrically robust framework to evaluate both in- and out-of-sample predictive performance, we show that our measures are not spanned by existing text and nontext variables.

We use a dynamic spatial general equilibrium model of international investment and production to investigate the real implications of the last five decades of financial globalization. We introduce a wedge accounting framework to estimate country- and time-varying measures of outward and inward Revealed Financial Openness (RFO). These wedges are meant to capture all impediments to cross-border investment, rather than explicit policy measures alone.

Projects with high societal impact--such as biodiversity conservation and climate change mitigation--often offer financial returns that are too low, or too risky, to attract private capital. Under such circumstances, it can be difficult to raise adequate financing for these projects. A potential solution is blended finance, that is, the blending of concessional funding (e.g., from governments, multilateral development banks, or philanthropies) with private capital.

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

The use of private capital to finance biodiversity conservation and restoration is a new practice in sustainable finance. This study sheds light on this new practice. First, we provide a conceptual framework that lays out how biodiversity can be financed by pure private capital and blended financing structures. In the latter, private capital is blended with public or philanthropic capital, whose aim is to de-risk private capital investments.

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.

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).