Markov Lecture

Markov Lecture

In 2005, the Applied Probability Society initiated the annual Markov Lecture, to be delivered in the fall of each year at the INFORMS Annual Meeting. The intent is to both honor the associated speaker and to bring to the APS membership topical work of the highest calibre in our discipline. The Markov Lecturer is selected by the APS prize committee.


2021 Markov Lecturer
Darrell Duffie
Adams Distinguished Professor of Management and Professor of Finance
Stanford University Graduate School of Business

2021 Markov Lecture Discussant
Mathieu Rosenbaum
Analytics and Models for Regulation Chair
Ecole Polytechnique

The recording of the 2021 Markov Lecture is available to watch here.

Title: Fragmenting Financial Markets

Abstract: This talk on financial market design addresses the costs (and sometimes the benefits) of fragmenting trade across multiple venues. Size discovery trading crosses buy and sell orders, with no bid-ask spread and no price impact, by exploiting the price determined on a separate exchange market. Although popular in practice, size discovery reduces the depth of exchange markets and, as modeled, worsens overall allocative efficiency. On the other hand, fragmenting trade in the same asset across multiple exchanges can improve allocative efficiency.

This talk draws from research with Samuel Antill, Daniel Chen, and Haoxiang Zhu.

Year Lecturer Affiliation Topic Discussant(s)
2020 Sem Borst Eindhoven University of Technology Neil Walton
2019 Laurent Massoulié INRIA Finding Structures Planted in Random Graphs Bruce Hajek
Jiaming Xu
2018 Sara van de Geer ETH Zurich Adaptive Estimation using Regularized Empirical Risk Alexandre Belloni
2017 Paul Dupuis Brown University Methods for Model Approximation and Optimization in the Presence of Model Uncertainty Using Information Divergences Markos Katsoulakis
2016 Gareth Roberts University of Warwick Piecewise deterministic Markov processes for Monte Carlo Natesh Pillai  
Jeff Rosenthal
2015 David Yao Columbia University Risk Analytics Jose Blanchet  
Paul Glasserman
2014 Peter Glynn Stanford University Perspectives on Traffic Modeling Assaf Zeevi
Pierre L'Ecuyer
2013 Martin Reiman Bell Labs A Stochastic Programming Based Approach to Assemble-to-Order Inventory Systems Alan Scheller-Wolf
Amy Ward
2012 Jim Dai Cornell University and Georgia Tech  Stochastic Network Models for Hospital Inpatient Flow Management
Part I
Part II              
Baris Ata
Avi Mandelbaum              
2011 Francois Baccelli ENS and INRIA Routing on Point Processes David Gramarnik
Devavrat Shah
2010 Ward Whitt Columbia University Multiserver Queues with Time-Varying Arrival Rates Galit Yom-Tov
Bill Massey
2009 John N. Tsitsiklis MIT Information Aggregation and Consensus in Networks
Part I
Part II
Part III              
Ben Van Roy
Vivek Borkar
2008 Steve Shreve CMU Mixing Models to Capture Stock Price Volatility Paul Glasserman
Ronnie Sircar
2007 Ruth Williams UCSD Stochastic Networks with Resource Sharing Kavita Ramanan
Mark Squillante
2006 Bruce Hajek UIUC

On Connections between Network Coding and Stochastic Network Theory: An Introduction

Michael Mitzenmacher
R.W.R. Darling
2005 Avi Mandelbaum Technion -- Israel Institute of Technology QED Q’s: Quality & Efficiency Driven Telephone Call/Contact Centers Ger Koole
Marty Reiman