The majority of my research is focused on econometrics, empirical macroeconomics and empirical finance, but my interests span a wide range of topics, including forecasting in a data-rich environment, the high-frequency effects of news announcements, term structure analysis and the econometrics of weak identification.
"Interest Rate Conundrums in the Twenty First Century" (joint with Sam Hanson and David Lucca)
"Jumps in Bond Yields at Known Times" (joint with Don Kim).
Material For Published Papers
Web Appendix for "The Economics of Options-Implied Inflation Probability Density Functions" (joint with Yuriy Kitsul)
180.367 - Investments and Portfolio Management
This is an introductory course in investments. The course is broken into four parts. The first part covers the fundamental concepts of asset returns, risk, and risk-aversion, and then studies how investors should optimally choose their portfolios given the observed patterns of risk and return. The second part of the course studies the reverse question: given how investors choose their portfolios, what are the equilibrium patterns of risk and expected return in financial markets: in other words, what is the expected return that various types of assets must earn to compensate investors for bearing their risk. The second question is studied in the context of two theories of returns: the capital asset pricing model and arbitrage pricing theory. The third part of the course studies the empirical evidence for and against the equilibrium theories of asset returns, with an emphasis on the evidence in support and against the efficient markets hypothesis. The fourth and final part of the course studies three classes of assets in more detail. The topics that are covered include models of equity valuation, bond valuation and hedging, and option valuation and hedging.
180.636 – Statistics
This course is a semester long introduction to probability theory and statistical inference for graduate students in
economics. The topics are prerequisties for subsequent econometrics courses. Topics include basic probability theory, estimation,
hypothesis testing, large sample theory, the bootstrap, and Bayesian approaches to inference.