Lawrence Schmidt

PhD Candidate – Department of Economics

Office: Ottersen Hall 4S124 / Econ 128

Email: lschmidt@ucsd.edu

Office Hours: By Appointment

University of California, San Diego
9500 Gilman Drive, Mail Code: 0534
La Jolla, CA 92093-0508

Degrees and Honors

2007 - B.A. in Economics-Mathematics, UC Santa Barbara:

Honors: Phi Beta Kappa, Overall and Departmental Academic Excellence Award

2011 - M.A. in Economics, UC San Diego

2012 - Advanced to Candidacy, UC San Diego

In Progress - Ph.D in Economics, UC San Diego

Honors: Walter P. Heller Best Third Year Paper Award (2012), Clive Granger Fellowship (2012), CPhil Fellowship (2012), National Science Foundation Graduate Research Fellowship Honorable Mention (2011), Graduate Core Teaching Assistant Excellence Award (2011), Undergraduate Teaching Assistant Excellence Award (2011), Graduate Summer Research Fellowship (2010, 2011)

Current Research Interests

Primary Fields: Financial Economics, Macroeconomics

Secondary Fields: Applied Econometrics

I am a PhD candidate in Economics at the University of California, San Diego. My research is at the intersection of finance and macroeconomics, with an emphasis on issues in asset pricing and banking. A common thread in my research agenda is the study of heterogeneity of households’ and financial institutions' risk exposures as manifested through conditional distributions and higher moments. These studies can reveal interesting asymmetries and nonlinearities and provide new insights about economic mechanisms, often without needing to impose strong assumptions on the data. My work helps to uncover new evidence on the nature of risk faced by financial market participants, such as the interaction between asset returns and idiosyncratic labor market risk and the strategic behavior of investors during the money market panic of 2008.

Research Papers

Runs on Money Market Mutual Funds

with Allan Timmermann and Russ Wermers

We study daily money market mutual fund flows at the individual share class level during the crisis of September 2008. The empirical approach that we apply to this fine granularity of data brings new insights into the investor and portfolio holding characteristics that are conducive to run-risk in cash-like asset pools, as well as providing evidence on the time-series dynamics of runs and the equilibria that develop. We find that outflows during the crisis are concentrated among those money funds with higher promised yields, less liquid portfolios, low implicit sponsor backing, and higher prior flow volatility that cater to very large-scale institutional investors. Our data uniquely allows us to study the strategic redemption behavior of investors with differing levels of sophistication by studying flows to different share classes of the same money fund, thus holding constant the quality of the underlying portfolio. Our results are consistent with the most sophisticated (largest scale) institutional investors exhibiting the greatest level of strategic redemptions during the crisis, which created significant negative externalities for more passive institutional investors.We study daily money market mutual fund flows at the individual share class level during the crisis of September 2008. The empirical approach that we apply to this fine granularity of data brings new insights into the investor and portfolio holding characteristics that are conducive to run-risk in cash-like asset pools, as well as providing evidence on the time-series dynamics of runs and the equilibria that develop. We find that outflows during the crisis are concentrated among those money funds with higher promised yields, less liquid portfolios, low implicit sponsor backing, and higher prior flow volatility that cater to very large-scale institutional investors. Our data uniquely allows us to study the strategic redemption behavior of investors with differing levels of sophistication by studying flows to different share classes of the same money fund, thus holding constant the quality of the underlying portfolio. Our results are consistent with the most sophisticated (largest scale) institutional investors exhibiting the greatest level of strategic redemptions during the crisis, which created significant negative externalities for more passive institutional investors.

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An Empirical Test of Pricing Kernel Monotonicity

with Brendan Beare, Working Paper

A large class of asset pricing models predict that securities which have high payoffs when market returns are low tend to be more valuable than those with high payoffs when market returns are high. More generally, we expect the pricing kernel to be a monotonically decreasing function of the market return. Numerous recent empirical studies appear to contradict this prediction. The nonmonotonicity of empirical pricing kernel estimates has become known as the pricing kernel puzzle. In this paper we propose and apply a formal statistical test of pricing kernel monotonicity. The test involves assessing the concavity of the ordinal dominance curve associated with the risk neutral and physical return distribution. We apply the test using thirteen years of data from the market for European put and call options written on the S&P 500 index. Statistically significant violations of pricing kernel monotonicity occur in a substantial proportion of months, suggesting that observed nonmonotonicities are real, and unlikely to be the product of statistical noise.

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Quantile Spacings: A Simple Method for the Joint Estimation of Multiple Quantiles

Walter P. Heller Memorial Award Winner for Best Third Year Paper

In a variety of economic applications, we would like to learn about aspects of a conditional distribution which are not well described by conditional means and/or variances. One simple econometric approach is to model a representative number of conditional quantiles. However, many existing methods suffer from the well-known quantile crossing problem, namely that the estimated quantile functions do not satisfy a basic monotonicity requirement that every quantile function must satisfy. We propose a simple but flexible parametric model for conditional quantiles. These quantiles will satisfy the monotonicity requirement by construction, so they are not susceptible to the quantile crossing problem. Rather than directly modeling the level of each individual quantile, we begin with a single quantile (usually the median), and then add or subtract nonnegative functions (quantile spacings) to obtain the other quantiles. We propose a simple interpolation method which generates a mapping from a finite number of quantiles to a probability density function. Two estimation methods are discussed in detail, and we characterize the limiting behavior of each. We identify a number of potential applications, and we highlight an application of the method by Schmidt, Timmermann, and Wermers (2013) to the study of a run on money market mutual funds in September 2008.

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Option Portfolio Selection Under Pricing Kernel Non-Monotonicity

with Brendan Beare, Working Paper (PAPER COMING SOON)

A recent literature in empirical finance documents the nonmonotone shape of pricing kernel estimates for several major market indices. In this paper we investigate the implications of pricing kernel nonmonotonicity for option portfolio choice. We propose a portfolio selection procedure that aims to deliver superior returns, relative to a direct market investment, by adapting to the shape of the pricing kernel. Numerical implementation of our procedure may be achieved using a multiobjective evolutionary algorithm. We investigate the out-of-sample performance of our portfolio selection procedure using twenty years of data from the market for European put and call options written on the S&P 500 index. Monthly portfolio returns outperform those of a direct market investment.

 

Climbing and Falling Off the Ladder: Asset Pricing Implications of Labor Market Event Risk

Job Market Paper, In Progress

Discrete events, particularly transitions between jobs, are thought to be one of the largest sources of wage dispersion. These switches often induce changes in wages that can be quite large, highly persistent, and largely uninsurable, particularly for individuals who are likely to invest in financial markets. Thus, labor market transitions can be idiosyncratic tail events, potentially having a disproportionate impact on welfare without affecting aggregate quantities. The nature of these events appears to be highly cyclical; transitions are much more likely to be favorable if they occur during expansions relative to recessions. As such, agents may require a premium for investing in assets which underperform when labor market event risk is high, a feature absent from leading asset pricing models. This paper explores the importance of this channel in affecting asset prices. We provide empirical evidence on the plausibility of event risk in explaining the shape of the idiosyncratic distribution of income growth rates as well as the relationship between event risk and aggregate variables. Next, we formalize its role within the context of a tractable asset pricing framework with heterogeneous agents and incomplete markets. Through the lens of this stylized model, we demonstrate the ways in which event risk can amplify risk premia relative to representative agent models. In addition, we explain how certain types of event risk can help generate hard-to-match features such as conditional heteroskedasticity of returns, an implied volatility smile, and a variance risk premium, even with Gaussian, homoscedastic fundamentals. Throughout, we make minimal assumptions on the dynamics of aggregate quantities, so that our results are immediately applicable to a wide class of existing representative agent models.

 

on The Dimensionality of Bounds Generated by the Shapley-Folkman Theorem

Journal of Mathematical Economics, January 2012

The Shapley-Folkman Theorem places a scalar upper bound on the distance between a sum of non-convex sets and its convex hull. We observe that some information is lost when a vector is converted to a scalar to generate this bound and propose a simple normalization of the underlying space which removes this loss of information. As an example, we apply this result to the Anderson (1978) core convergence theorem, and demonstrate how our normalization leads to an intuitive, unitless upper bound on the discrepancy between an arbitrary core allocation and the corresponding competitive equilibrium allocation.

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One Solution to the Option Pricing Overvaluation Problem: Using Down and Out Call Options

with Ronald Schmidt, Business Valuation Update, May 2011

Recent articles have pointed to concerns about the validity of using option pricing models (OPM) to determine the value of common stock in 409(a) valuations. At issue is the question of whether OPMs provide appropriate methodologies to establish the appropriate fair market value of common stock. Specifically, use of standard Black-Scholes algorithms will overstate the value of common stock by not properly modeling the impact of failure scenarios. We argue that claims to equity of early-stage companies may be more appropriately modeled as “down and out” call options, rather than traditional European call options (as required by the Black-Scholes formula). Like Black-Scholes, these options still have the benefit of a simple, closed-form solution, but they better account for the path dependence of enterprise value and allow for a higher probability of failure. We demonstrate that these alternative option pricing models can be used to either estimate enterprise value (back-solving) or to allocate value, and that their use can result in more reasonable estimates of common stock when compared with Black-Scholes.

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Teaching

Graduate Teaching Assistant Positions

  • MGT 281 - Investments, Professor Allan Timmermann (Fall 2011, 2012, and 2013)
  • Econ 200B - Graduate Micoreconomics Core, Professors Mark Machina and Joel Watson (Winter 2011)
  • MGT 283 - Financial Risk Management, Professor Rossen Valkanov (Winter 2011, Spring 2012)
  • MGT 280 - New Venture Finance, Professor Dongmei Li (Fall 2010)
  • Econ 205 - Mathematics for Economists, Professor Joel Sobel (Summer 2010)

Undergraduate Teaching Assistant Positions

  • Econ 100A - Microeconomics, Professor Michael Noel (Fall, Winter 2010) and Professor James Andreoni (Winter 2012)
  • Econ 171 - Decisions Under Uncertainty, Professor Herb Newhouse (Spring 2010, 2012, and 2013) and Professor Christopher Chambers (Winter 2013)
  • Econ 100B - Microeconomics, Professor Mark Jacobsen (Fall 2009)

Links

LinkedIn profile: http://www.linkedin.com/in/lawrenceschmidt