Nick Polson

University of Chicago - Booth School of Business

Associate Professor of Statistics

5807 S. Woodlawn Avenue

Chicago, IL 60637

United States

  • University of Chicago - Booth School of Business

    • Email
    • Tel: 773-702-7513
    • Fax: 773-702-0458
SCHOLARLY PAPERS

19

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CITATIONS
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469

Scholarly Papers (19)

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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
J.B. Heaton, P.C., University of Chicago - Booth School of Business and University College London - Department of Mathematics
Downloads 6,727 (859)

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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
J.B. Heaton, P.C., University of Chicago - Booth School of Business and University College London - Department of Mathematics
Downloads 5,826 (1,107)

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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 2,029 (6,802)
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 1,574 (10,413)
Citation 10

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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
Michael S. Johannes, Arthur G. Korteweg and Nick Polson
Columbia Business School - Finance and Economics, University of Southern California - Marshall School of Business and University of Chicago - Booth School of Business
Downloads 1,512 (11,115)
Citation 9

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Learning, predictability, optimal portfolio formation

6.

Sequential Optimal Portfolio Performance: Market and Volatility Timing

Number of pages: 48 Posted: 24 Mar 2002
Michael S. Johannes, Nick Polson and Jonathan R Stroud
Columbia Business School - Finance and Economics, University of Chicago - Booth School of Business and McDonough School of Business, Georgetown University
Downloads 1,047 (19,644)
Citation 28

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7.

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 1,015 (20,576)
Citation 59

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

8.

The Impact of Jumps in Volatility and Returns

Downloads 994 ( 21,244)
Citation 285

The Impact of Jumps in Volatility and Returns

Number of pages: 47 Posted: 01 Jan 2001
Michael S. Johannes, Bjorn Eraker and Nick Polson
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 994 (20,881)
Citation 285

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

The Impact of Jumps in Volatility and Returns

Journal of Finance, Vol. 58, pp. 1269-1300, June 2003
Posted: 31 Aug 2003
Bjorn Eraker, Michael S. Johannes and Nick Polson
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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9.

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 600 (42,772)
Citation 7

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Sequential learning, filtering, stochastic volatility, Kalman filter

10.

Nonlinear Filtering of Stochastic Differential Equations with Jumps

Number of pages: 44 Posted: 15 Oct 2002
Michael S. Johannes, Jonathan R Stroud and Nick Polson
Columbia Business School - Finance and Economics, McDonough School of Business, Georgetown University and University of Chicago - Booth School of Business
Downloads 563 (46,459)
Citation 6

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

11.

Tracking Flu Epidemics Using Google Flu Trends and Particle Learning

Number of pages: 33 Posted: 27 Nov 2009 Last Revised: 27 Oct 2012
Vanja M. Dukic, Hedibert F. Lopes and Nick Polson
University of Chicago, University of Chicago - Booth School of Business and University of Chicago - Booth School of Business
Downloads 440 (63,306)

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

12.

Deep Learning in Asset Pricing

Number of pages: 33 Posted: 23 Sep 2018 Last Revised: 09 Feb 2019
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 425 (66,756)

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Alpha, Cross-Sectional Returns, Deep Learning, Firm Characteristics, Machine Learning, Risk Factors, Security Sorting.

13.

Smart Money, Dumb Money, and Learning Type from Price

Number of pages: 23 Posted: 09 Aug 2011 Last Revised: 18 Feb 2019
J.B. Heaton and Nick Polson
J.B. Heaton, P.C. and University of Chicago - Booth School of Business
Downloads 282 (105,232)

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smart money, dumb money, noise traders, limits of arbitrage, learning, heterogeneous beliefs

14.

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
Carlos M. Carvalho, Michael S. Johannes, Hedibert F. Lopes and Nick Polson
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 216 (137,954)
Citation 6

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15.

Quantile Filtering and Learning

Number of pages: 40 Posted: 21 Nov 2009
Michael S. Johannes, Nick Polson and Seung M. Yae
Columbia Business School - Finance and Economics, University of Chicago - Booth School of Business and University of Chicago - Booth School of Business
Downloads 173 (169,231)

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

16.

Sequential Inference for Nonlinear Models using Slice Variables

Number of pages: 35 Posted: 21 Nov 2009
Michael S. Johannes, Nick Polson and Seung M. Yae
Columbia Business School - Finance and Economics, University of Chicago - Booth School of Business and University of Chicago - Booth School of Business
Downloads 111 (241,128)

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

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 71 (319,554)

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

18.

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 64 (337,614)

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

19.

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
Michael S. Johannes, Nick Polson and Jonathan R Stroud
Columbia Business School - Finance and Economics, University of Chicago - Booth School of Business and McDonough School of Business, Georgetown University

Abstract:

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