Nick Polson

University of Chicago - Booth School of Business

Associate Professor of Statistics

5807 S. Woodlawn Avenue

Chicago, IL 60637

United States

SCHOLARLY PAPERS

18

DOWNLOADS
Rank 1,159

SSRN RANKINGS

Top 1,159

in Total Papers Downloads

28,670

SSRN CITATIONS
Rank 4,433

SSRN RANKINGS

Top 4,433

in Total Papers Citations

214

CROSSREF CITATIONS

96

Scholarly Papers (18)

1.

Deep Learning for Finance: Deep Portfolios

Applied Stochastic Models in Business and Industry 33 (1), 3-12.
Number of pages: 15 Posted: 14 Sep 2016 Last Revised: 29 Apr 2019
J.B. Heaton, Nick Polson and Jan Witte
One Hat Research LLC, University of Chicago - Booth School of Business and University College London - Department of Mathematics
Downloads 9,372 (676)
Citation 46

Abstract:

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Deep Learning, Machine Learning, Big Data, Artificial Intelligence, Finance, Asset Pricing, Volatility, Deep Frontier

2.

Why Indexing Works

Applied Stochastic Models in Business and Industry 33 (6), 690-693.
Number of pages: 7 Posted: 14 Oct 2015 Last Revised: 29 Apr 2019
J.B. Heaton, Nick Polson and Jan Witte
One Hat Research LLC, University of Chicago - Booth School of Business and University College London - Department of Mathematics
Downloads 6,738 (1,213)
Citation 3

Abstract:

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Indexing, Passive Management, Active Management

3.

MCMC Methods for Continuous-Time Financial Econometrics

Number of pages: 96 Posted: 27 Dec 2003
Michael S. Johannes and Nick Polson
Columbia Business School - Finance and Economics and University of Chicago - Booth School of Business
Downloads 2,130 (8,593)
Citation 59

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4.

Corporate Credit Spreads under Parameter Uncertainty

AFA 2009 San Francisco Meetings Paper
Number of pages: 45 Posted: 26 Mar 2008 Last Revised: 30 Nov 2009
Arthur G. Korteweg and Nick Polson
University of Southern California - Marshall School of Business and University of Chicago - Booth School of Business
Downloads 1,623 (13,335)
Citation 11

Abstract:

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Credit risk, credit spread, bankruptcy, default, corporate bonds, MCMC

5.

Sequential Learning, Predictability, and Optimal Portfolio Returns

Journal of Finance, Forthcoming, AFA 2009 San Francisco Meetings Paper
Number of pages: 58 Posted: 25 Mar 2008 Last Revised: 04 Apr 2013
Columbia Business School - Finance and Economics, University of Southern California - Marshall School of Business and University of Chicago - Booth School of Business
Downloads 1,566 (14,095)
Citation 42

Abstract:

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Learning, predictability, optimal portfolio formation

6.

Deep Learning in Characteristics-Sorted Factor Models

Number of pages: 40 Posted: 23 Sep 2018 Last Revised: 22 Feb 2021
Guanhao Feng, Nick Polson and Jianeng Xu
City University of Hong Kong (CityUHK), University of Chicago - Booth School of Business and University of Chicago, Students
Downloads 1,462 (15,780)
Citation 7

Abstract:

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Alpha, Characteristics-Sorted Factor Models, Cross-Sectional Returns, Deep Learning, Firm Characteristics, Non-Arbitrage, Pricing Errors.

7.
Downloads 1,120 ( 23,506)
Citation 52

The Impact of Jumps in Volatility and Returns

Number of pages: 47 Posted: 01 Jan 2001
Columbia Business School - Finance and Economics, University of Wisconsin - Madison - Department of Finance, Investment and Banking and University of Chicago - Booth School of Business
Downloads 1,120 (23,118)
Citation 52

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Jumps, Stochastic Volatility, Continuous-Time Econometrics, Option Pricing, Market Stress

The Impact of Jumps in Volatility and Returns

Posted: 31 Aug 2003
University of Wisconsin - Madison - Department of Finance, Investment and Banking, Columbia Business School - Finance and Economics and University of Chicago - Booth School of Business

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8.

Sequential Optimal Portfolio Performance: Market and Volatility Timing

Number of pages: 48 Posted: 24 Mar 2002
Columbia Business School - Finance and Economics, University of Chicago - Booth School of Business and McDonough School of Business, Georgetown University
Downloads 1,113 (23,726)
Citation 43

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9.

Bayesian Analysis of a Stochastic Volatility Model with Leverage Effect and Fat Tails

Boston College Finance Dept. Working Paper
Number of pages: 31 Posted: 16 Jul 2001
Eric Jacquier, Peter E. Rossi and Nick Polson
Boston University School of Management, University of California, Los Angeles (UCLA) - Anderson School of Management and University of Chicago - Booth School of Business
Downloads 1,055 (25,659)
Citation 69

Abstract:

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ARCH, Bayes factor, Fat-tails, Gibbs Leverage effect, Metropolis, MCMC, Stochastic volatility

10.

Particle Filtering and Parameter Learning

Number of pages: 39 Posted: 02 May 2007
Michael S. Johannes and Nick Polson
Columbia Business School - Finance and Economics and University of Chicago - Booth School of Business
Downloads 626 (52,634)
Citation 11

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Sequential learning, filtering, stochastic volatility, Kalman filter

11.

Nonlinear Filtering of Stochastic Differential Equations with Jumps

Number of pages: 44 Posted: 15 Oct 2002
Columbia Business School - Finance and Economics, McDonough School of Business, Georgetown University and University of Chicago - Booth School of Business
Downloads 587 (57,104)
Citation 11

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Filtering, Stochastic Differential Equations, Jumps, Option Pricing, Volatility

12.

Tracking Flu Epidemics Using Google Flu Trends and Particle Learning

Number of pages: 33 Posted: 27 Nov 2009 Last Revised: 27 Oct 2012
University of Chicago, University of Chicago - Booth School of Business and University of Chicago - Booth School of Business
Downloads 519 (66,515)
Citation 6

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Epidemics, Particle learning, influenza, Google, IP surveillance, SEIR, H1N1 virus

13.

Particle Learning and Smoothing

Statistical Science, Vol. 25, No. 1, pp. 88-106, 2010
Number of pages: 19 Posted: 22 Oct 2011 Last Revised: 09 Nov 2011
University of Texas at Austin - Red McCombs School of Business, Columbia Business School - Finance and Economics, University of Chicago - Booth School of Business and University of Chicago - Booth School of Business
Downloads 234 (161,002)

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14.

Quantile Filtering and Learning

Number of pages: 40 Posted: 21 Nov 2009
Columbia Business School - Finance and Economics, University of Chicago - Booth School of Business and University of Chicago - Booth School of Business
Downloads 186 (199,293)
Citation 1

Abstract:

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Quantile, LAD, Particle Filtering, Particle Learning, Bayes Factor

15.

Sequential Inference for Nonlinear Models using Slice Variables

Number of pages: 35 Posted: 21 Nov 2009
Columbia Business School - Finance and Economics, University of Chicago - Booth School of Business and University of Chicago - Booth School of Business
Downloads 119 (286,141)
Citation 1

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Monte Carlo, Particle Filtering, Particle Learning, Nonlinear State Space Model, Slice Variable

16.

Sparse Regularization in Marketing and Economics

Number of pages: 29 Posted: 20 Aug 2017 Last Revised: 10 Feb 2018
Guanhao Feng, Nick Polson, Yuexi Wang and Jianeng Xu
City University of Hong Kong (CityUHK), University of Chicago - Booth School of Business, University of Chicago, Students and University of Chicago, Students
Downloads 111 (300,273)

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Machine learning, Regularization, Proximal Algorithm, Nonconvex Optimization, Marketing Demand Forecasting

17.

Regularizing Bayesian Predictive Regressions

Number of pages: 35 Posted: 17 Aug 2016 Last Revised: 15 Sep 2017
Guanhao Feng and Nick Polson
City University of Hong Kong (CityUHK) and University of Chicago - Booth School of Business
Downloads 109 (306,045)
Citation 1

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Bayesian predictive regression; prior sensitivity analysis; maximum-a-posteriori; equity-premium predictability; bond risk premia; predictor selection.

18.

Optimal Filtering of Jump Diffusions: Extracting Latent States from Asset Prices

The Review of Financial Studies, Vol. 22, Issue 7, pp. 2559-2599, 2009
Posted: 22 Jun 2009
Columbia Business School - Finance and Economics, University of Chicago - Booth School of Business and McDonough School of Business, Georgetown University

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C11, C13, C15, C51, C52, G11, G12, G17