Weekly Seminars 2017-2018
Seminars for 2017-2018
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Approaching Mean-Variance Efficiency for Large Portfolios
November 9, 2017 – 11:00 am to noon
Department of Finance and Risk Engineering, Tandon School of Engineering, New York University
Do Marginal Products Differ from User Costs? Micro-Level Evidence from Italian Firms
Using micro-data on firm-specific borrowing costs and wages, we demonstrate that distortions in firms’ employment and investment policies can be empirically measured using firm-level gaps between marginal revenue products and user costs (MRP-cost gaps). We estimate MRP-cost gaps for 4 million firm-year observations in Italy between 1997 and 2013, showing that the variation in these measures is closely related to the extent of credit market frictions and to the degree of labor market rigidities faced by individual firms. Using the estimated MRP-cost gaps, we propose a reallocation algorithm that helps us assess the scope of capital and labor misallocation in Italy, and its impact on aggregate output and Total Factor Productivity (TFP). We calculate that, holding constant the aggregate capital and labor endowments in the economy, the Italian corporate sector could produce between 3 to 4 percent more output by reallocating resources from over-endowed producers toward higher value users. The output losses from misallocation are larger during episodes of macro-financial instability, in non-manufacturing industries, and in geographical regions with less developed socio-economic institutions.
January 4, 2018 – 11:00 am-noon
Polsky Center for Entrepreneurship and Innovation, The University of Chicago
An Introduction to Entrepreneurial Resources at the University
A Portfolio Perspective on the Multitude of Firm Characteristics
February 1, 2018 – 11:30am-12:30pm
Willem van Vliet
Department of Economics and Booth School of Business, University of Chicago
Estimating Bank Interconnectedness from Market Data
February 13, 2018 – 11:30am-12:30pm
Department of Economics and Bendheim Center for Finance, Princeton University
Closed-Form Implied Volatility Surfaces for Stochastic Volatility (with Chenxu Li and Chen Xu Li)
February 15, 2018 – 11:30am-12:30pm
Institut für Matematik, Humoldt-Universität zu Berlin
Volatility estimation under one-sided errors with applications to limit order books (joint with M. Bibinger, M. Jirak)
February 22, 2018 – 11:30am-12:30pm
Department of Management Science and Engineering, Stanford University
Estimating Latent Asset-Pricing Factors (joint with Martin Lettau, UC Berkeley)
March 8, 2018 – 11:30am-12:30pm
Noureddine El Karoui
Department of Statistics, University of California, Berkeley
Can we trust the bootstrap (for moderately difficult statistics problems)? Based on joint papers with Elizabeth Purdom, UC Berkeley.
Our assessment will be done through a mix of numerical and theoretical investigations. The theory will be developed under the assumptions that the ratio of number of predictors to number of observations is kept fixed in our asymptotics. This is a way to keep the “statistical difficulty” of the problem fixed in the asymptotics. These asymptotic results tend to reflect the finite sample behavior of statistical methods better than traditional asymptotics.
Interestingly, bootstrap methods that are thought to be perform equivalently well for inference -based on classical asymptotic arguments- will be shown to have very different behavior numerically and in our theoretical framework. For instance, some are very conservative and some are very anti-conservative, while they are equally “intuitive”. I will also discuss the behavior of other resampling plans, such as the jackknife, as well as ways to fix some of the problems we have identified.
Multi-armed Bandits and Optimal Sequential Treatment Allocation with General Welfare Measures
April 2, 2018 – 4:30 pm to 5:30 pm – Eckhart Hall, Room 133, 5801 S. Ellis Ave, University of Chicago Campus
This seminar is organized jointly by the Stevanovich Center and the UC Department of Statistics
Executive director of Tencent AI Lab and former professor at Rutgers University
Modern Stochastics Optimization Methods for Big Data Machine Learning
Estimating the Dynamics of Consumption Growth
April 12, 2018 – 11am to noon
Geneva Finance Research Institute, University of Geneva, and Swiss Finance Institute