Lin William Cong is a professor of Finance and PhD advisor at the University of Chicago, and a faculty affiliate at the Center for East Asian Studies. His research interests include real options, entrepreneurial finance, market efficiency, statistical learning, financial intermediation and innovation, and China's economy and financial markets. For his doctoral studies, Cong has received the Finance Theory Group Best Paper Award, the Shmuel Kandel Award, and the Zephyr Prize for Best Paper in Corporate Finance, amongst other honors and fellowships. He was also a George Shultz Scholar at the Stanford Institute for Economic Policy Research and a PhD Fellow at the Stanford Institute for Innovation in Developing Economies, with research grants from both institutes. Additionally, his undergraduate research in physics and applied mathematics resulted in publications in a variety of science journals. Cong currently referees for The American Economic Review, Review of Financial Studies, Management Science, Journal of Economic Theory, and Journal of Political Economy. He also serves as a member of the American Economic Association, European Finance Association, the Econometric Society, and the Society of Financial Studies.
Cong earned a Ph.D. in finance and a MS in statistics from Stanford University, where he received the Gerald Lieberman Fellowship for outstanding contributions in research, teaching, and university service, and the Asian American Award for graduate leadership. He also holds dual degrees from Harvard University where he graduated top in Physics in 2009 with summa cum laude and Phi Beta Kappa, receiving an A.M. in physics, an A.B. in math & physics, a minor in economics, and a language citation in French.
Cong is a native of Shenyang, China. Outside his research and teaching, Cong practices Chinese Calligraphy, and enjoys reading, sports, cross fitness, guitar, as well as learning French and Japanese. Cong is also passionate about education in China and in the U.S., and integrating quantitative and fundamental approaches to investments in various asset classes, to which he coined the term "Quantimental Investing."
2016 - 2017 Course Schedule
REVISION: Rise of Factor Investing: Asset Prices, Informational Efficiency, and Security Design
We model financial innovations such as Exchange-Traded Funds, smart beta products, and many index-based vehicles as composite securities that facilitate trading common factors in assets' liquidation values. Through accessing a larger basket of assets in endogenously-chosen proportions, composite securities can benefit both informed and liquidity traders and attract all factor investors with optimal designs that feature selecting liquid and representative assets. Consistent with empirical findings, introducing composite securities leads to higher price variability and co-movements, larger trading costs and synchronicity, and lower asset-specific but higher factor information in prices, especially for illiquid assets. Trading transparency, distinction between bundles and derivatives, and endogenous information acquisition also significantly affect prices and security design.
REVISION: Intervention Policy in a Dynamic Environment: Coordination and Learning
We model a dynamic economy with strategic complementarity among investors and endogenous government interventions that mitigate coordination failures. We establish equilibrium existence and uniqueness, and show that one intervention can affect subsequent interventions through altering public information structures. Our results suggest that optimal policy often emphasize initial interventions because coordination outcomes tend to correlate. Neglecting informational externalities of initial interventions results in over- or under-interventions depending on intervention costs. Moreover, saving smaller funds before saving the big ones under certain circumstances costs less and generates greater informational benefits. Our paper is applicable to intervention programs such as those during the 2008 financial crisis.
New: Credit Allocation under Economic Stimulus: Evidence from China
We study credit allocation across firms in developing economies with severe financial frictions. We illustrate the effects of financial frictions on credit allocation in a dynamic setting, and find that credit expansions during recessions can slow down or even reverse the gradual reallocation of resources from low to high productivity firms. We test the model empirically using China’s economic stimulus plan introduced in 2008, which triggered an unprecedented policy-driven credit expansion. Using private firm-level data we show that new credit was allocated disproportionately more towards state-owned, low-productivity firms than to privately-owned, high-productivity firms, with significant impact on the real economy.
REVISION: Auctions of Real Options
Governments and corporations frequently sell assets with embedded real options to competing buyers using security bids. Examples include the sales of natural resources, real estate, patents and licenses, and start-up companies. This paper models these auctions of real options, incorporating both endogenous auction timing and post-auction option exercise. I characterize the ways common security bids distort investments and strategic auction timing affects auction initiation, security ranking, equilibrium bidding, and investment. Revenue-maximizing sellers inefficiently delay auctions, including optimal auctions which align investment incentives using a combination of down payment and royalty payment. When sellers do not restrict security design, bidding and allocation outcomes are equivalent to cash auctions. Finally, informed bidders always initiate the auctions when they could. The results are broadly consistent with empirical observations and underscore that auction timing and ...