Lukas Schmid, USC Marshall School of Business)

What are your current research themes?

Much of my current research is concerned with understanding investor behavior in bond markets and its implications for the real economy. In contrast to equity markets, bond markets are largely dominated by institutional investors rather than retail investors. In corporate bond markets, insurance companies, pensions, and increasingly, mutual funds, are important players, while in government bond markets, foreign investors, including foreign central banks, and, increasingly, the Federal Reserve, play an important role. What are these investors’ objectives, how can we describe them, and how do they affect the costs of funding for corporations and the government?  In some ongoing work with my fantastic co-authors, I’m trying to get make some sense of these questions. This involves a lot of data work, by collecting large amounts of data showing what kind of securities institutions end up buying and selling, and a lot of modeling, in order to understand why they choose to hold them given the constraints they face. Regarding the corporate bond market (in the paper ‘Passive Demand and Active Supply: Evidence from Maturity-Mandated Corporate Bond Funds’, with Lorenzo Bretscher and Tiange Ye), we show that corporate bond mutual funds that are mandated to buy bonds within a certain maturity spectrum create buying and price pressure for bonds that become available to them, and that corporations respond to that price pressure by issuing new bonds at favorable prices. Interestingly, we find that constrained companies use the proceeds of these issuances to fund real investment. Regarding the government bond market (in the paper ‘Granular Treasury Demand with Arbitrageurs’, with Kristy Jansen and Wenhao Li), we show that hedge funds and dealers play an important role as arbitrageurs and that their risk-bearing capacity depends critically on macroeconomic conditions. Understanding investor behavior in U.S. Treasury markets is especially important in view of the projections that the U.S. debt-to-gdp ratio is expected to rise to about 150 percent by 2050. Which investors will buy all these bonds? In our work, we give a quantitative perspective on this question. 

In a recent article of the Journal of Finance, you and co-authors offer a novel approach to measure the term structure of covered interest rate parity violations. Could you share with us what this approach consists of and what are your findings?

In this paper, we revisit covered interest parity (CIP) violations, which are often viewed as prima facie evidence that intermediary constraints matter for asset valuation, as these apparent arbitrage opportunities should not persist in frictionless environments. In our analysis, we develop a novel approach to measuring potential arbitrage returns that suggests that what appear to be violations of covered interest parity may not actually be arbitrage opportunities after all. Typically, to test for potential covered interest parity violations (to identify a potentially successful interest rate arbitrage across currencies) for short-term transactions, one compares bank funding rates, such as LIBOR, as a proxy for the countries’ respective interest rates. To evaluate trades longer than one year, one uses pricing of foreign exchange derivative instruments called cross-currency basis swaps, since LIBOR rates only go out 12 months.
However, there is significant evidence that bank funding rates -- rates at which large banks lend to one another; LIBOR is a benchmark for the average of this rate for London banks -- might not be appropriate to use. That is because those rates may include the risk of default by a bank, and that risk varies greatly between countries.  So, we set aside bank funding rates and cross-currency swap rates, and instead, we extract our own effective funding rates using each country’s interest rate swaps over various maturities. We are thus able to infer interest rates (at different maturities) for each country from interest rate swaps. These rates are used to convert the value of future cash flows into today’s current value. Using the calculated current values for the cash flows on each side of an exchange of currencies, say one side with cash flows for the U.S. dollar and the other side with cash flows for the Euro, a cross currency rate can be estimated. These estimated cross currency rates are then compared back to the market’s actual forward exchange rates and closely track the actual forward exchange rates. The improved tracking is due to the fact that the rates inferred by us are different from the observed LIBOR rates, which primarily reflect bank default risk. The inferred rates also reflect other risks associated with a country’s Treasury yield convenience and sovereign default risk. Once these “more correct” rates are used, the arbitrage opportunities mostly disappear.
Our funding model explains away all short-term covered interest parity deviations and about two-thirds of the longer-term deviations. In other words, these anomalies may not be covered interest parity violations – arbitrage opportunities -- at all.  That leaves one-third of the longer-term potential trades to explain. Why do these seemingly profitable arbitrage opportunities persist? Here we conjecture that the remaining errors are due to constraints – complexities in the markets and among intermediaries that cause friction to transactions such that the seemingly profitable trades cannot effectively be executed.

You recently taught in our PhD Programme a course on models and tools in dynamic macro-finance. What have you emphasized in this course?

My objective in my PhD courses is to introduce students to some tools they can use in their research, or, ideally, that help them get started in their research. Therefore, I try to adopt a hands-on approach in my classes. I typically start by introducing some big picture questions and then walk the students through some methods that they can use to tackle these questions. That involves running some computer codes implementing these tools in class. My hope is that the students can take these codes, modify them according to their needs, and use them as a starting point to answer questions that they want to tackle in their own research. 

Our PhD in Finance is mainly open to professionals. How does this programme compare to a traditional full-time PhD programme?

I think that financial economics is very much an applied subject that heavily benefits from integrating the different perspectives of practitioners and academics, and I believe that the PhD programme at EDHEC is an ideal environment to facilitate such interaction. As an example, in my own work in institutional investors in corporate bond markets, it has become increasingly clear that institutional and regulatory constraints are important determinants of investor behavior and prices, and interacting with practitioners taught me a great deal about what drives such constraints.  

As a leading academic scholar and as an editor for the Finance area of Management Science, a leading peer-reviewed academic journal, what advice can you give to our PhD candidates who would like to publish their research?

My advice to young researchers sounds a bit trite but true, in that I always encourage them to work only on questions that they really want to answer. They need to really want to know that answer. If they do not care much about the answer to a particular question, then there is no point in working on it no matter how fashionable or in-demand a particular area is at the time. Publishing takes a lot of effort and perseverance, and editors and referees may keep pushing back and ask for changes and further analysis. So it takes energy to get to the end, and in my own work, I really can only find that energy when I deeply care. 

Lukas Schmid is Professor of Finance and Business Economics at the Marshall School of Business, University of Southern California, and a CEPR Research Fellow. Before joining Marshall, Lukas spent a decade at the Fuqua School of Business at Duke University. He currently serves as an Editor for the Finance Area at Management Science. Lukas' research interests are in dynamic quantitative modeling and structural estimation applied at the intersection of macroeconomics and financial economics. His most recent work was concerned with corporate and sovereign default and credit risk, as well as links between innovation, long-run growth and financial market performance. Lukas’ research has been published in outlets such as the American Economic Review, the Journal of Finance, the Journal of Financial Economics, the Review of Financial Studies and the Journal of Monetary Economics. His work on capital structure and asset returns was awarded a Smith-Breeden Award (First Prize) for the best paper in the Journal of Finance, 2010. At Marshall, he teaches investments to undergraduate students and advanced asset pricing to PhD students. Lukas obtained a master’s degree in mathematics from ETH Zurich and a PhD in Finance from the University of Lausanne & Swiss Finance Institute.