Gordon Ritter

New York University (NYU) - Courant Institute of Mathematical Sciences

Adjunct Professor

New York University

251 Mercer Street

New York, NY 10012

United States

City University of New York (CUNY) - Weissman School of Arts and Sciences

One Bernard Baruch Way

New York, NY 10010

United States

Rutgers, The State University of New Jersey - Financial Statistics & Risk Management

Professor of Practice

110 Frelinghuysen Road

479 Hill Center, Busch Campus

Piscataway, NJ 08854

United States

New York University (NYU) - NYU Tandon School of Engineering

6 MetroTech Center

Brooklyn, NY 11201

United States

SCHOLARLY PAPERS

11

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Top 2,278

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18,192

SSRN CITATIONS
Rank 35,218

SSRN RANKINGS

Top 35,218

in Total Papers Citations

9

CROSSREF CITATIONS

14

Scholarly Papers (11)

1.

Machine Learning for Trading

Number of pages: 19 Posted: 14 Aug 2017 Last Revised: 04 Dec 2017
Gordon Ritter
New York University (NYU) - Courant Institute of Mathematical Sciences
Downloads 11,082 (506)
Citation 16

Abstract:

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Finance, Investment Analysis, Machine Learning, Portfolio Optimization

2.

Modern Perspectives on Reinforcement Learning in Finance

The Journal of Machine Learning in Finance, Vol. 1, No. 1, 2020.
Number of pages: 28 Posted: 16 Sep 2019 Last Revised: 16 Mar 2021
Petter N. Kolm and Gordon Ritter
New York University (NYU) - Courant Institute of Mathematical Sciences and New York University (NYU) - Courant Institute of Mathematical Sciences
Downloads 2,320 (7,473)
Citation 5

Abstract:

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Dynamic programming, Finance, Hedging, Intertemporal choice; Investment analysis, Machine learning, Optimal control, Options, Portfolio optimization, Reinforcement learning

3.

Multiperiod Portfolio Selection and Bayesian Dynamic Models

Risk, Vol. 28, Issue 3, p 50-54, March 2015
Number of pages: 8 Posted: 28 Jul 2014 Last Revised: 16 Mar 2021
Petter N. Kolm and Gordon Ritter
New York University (NYU) - Courant Institute of Mathematical Sciences and New York University (NYU) - Courant Institute of Mathematical Sciences
Downloads 2,173 (8,309)
Citation 1

Abstract:

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Portfolio optimization, Transaction costs, Bayesian statistics, Markov models

4.

On the Bayesian Interpretation of Black-Litterman

European Journal of Operational Research, Volume 258, Issue 2, 16 April 2017, Pages 564-572
Number of pages: 22 Posted: 17 Oct 2016 Last Revised: 01 Dec 2017
Petter N. Kolm and Gordon Ritter
New York University (NYU) - Courant Institute of Mathematical Sciences and New York University (NYU) - Courant Institute of Mathematical Sciences
Downloads 1,033 (26,401)
Citation 2

Abstract:

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Black-Litterman, Portfolio Optimization, APT, Bayesian statistics

5.

Optimal Microstructure Trading with a Long-Term Utility Function

Number of pages: 26 Posted: 24 Oct 2017 Last Revised: 03 Dec 2017
Elie Benveniste and Gordon Ritter
New York University (NYU) - Courant Institute of Mathematical Sciences and New York University (NYU) - Courant Institute of Mathematical Sciences
Downloads 644 (50,587)
Citation 1

Abstract:

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Finance, Investment Analysis, Optimal Execution, Market Microstructure

6.

Stable Linear-Time Optimization in Arbitrage Pricing Theory Models

Risk Magazine, 2016
Number of pages: 9 Posted: 12 Aug 2016
Gordon Ritter
New York University (NYU) - Courant Institute of Mathematical Sciences
Downloads 583 (57,515)

Abstract:

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Portfolio Optimization

7.

A New Copula for Modeling Tail Dependence

Number of pages: 29 Posted: 26 Aug 2010 Last Revised: 15 Nov 2010
Jeff Holman and Gordon Ritter
Highbridge Capital Management and New York University (NYU) - Courant Institute of Mathematical Sciences
Downloads 357 (103,494)

Abstract:

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8.

Black-Litterman and Beyond: The Bayesian Paradigm in Investment Management

The Journal of Portfolio Management, to appear, 2021.
Posted: 09 Mar 2021
Petter N. Kolm, Gordon Ritter and Joseph Simonian
New York University (NYU) - Courant Institute of Mathematical Sciences, New York University (NYU) - Courant Institute of Mathematical Sciences and Natixis Investment Managers, L.P.

Abstract:

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Bayesian statistics, Black-Litterman, Factor investing, Investment management, Portfolio optimization, Portfolio theory, Risk premia, Robust portfolio management, Trading, Transaction costs, Views

9.

Factor Investing with Black-Litterman-Bayes: Incorporating Factor Views and Priors in Portfolio Construction

The Journal of Portfolio Management, Special Issue on Factor Investing, 2021
Posted: 03 Feb 2021
Petter N. Kolm and Gordon Ritter
New York University (NYU) - Courant Institute of Mathematical Sciences and New York University (NYU) - Courant Institute of Mathematical Sciences

Abstract:

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Factor investing, Investment analysis, Bayesian statistics, Black-Litterman, Portfolio optimization, Portfolio theory, Risk premia

10.

Deep Reinforcement Learning for Option Replication and Hedging

Jiayi Du, Muyang Jin, Petter N. Kolm, Gordon Ritter, Yixuan Wang and Bofei Zhang, 'Deep Reinforcement Learning for Option Replication and Hedging.' The Journal of Financial Data Science 2.4 (2020).
Posted: 21 Oct 2020
New York University (NYU) - Center for Data Science, New York University (NYU) - Center for Data Science, New York University (NYU) - Courant Institute of Mathematical Sciences, New York University (NYU) - Courant Institute of Mathematical Sciences, New York University (NYU) - Center for Data Science and New York University (NYU) - Center for Data Science

Abstract:

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Financial Machine Learning, Hedging, Deep Q-learning, Deep Reinforcement Learning, Deep Neural Networks, Option Replication, Proximal Policy Optimization

11.

Dynamic Replication and Hedging: A Reinforcement Learning Approach

Kolm, Petter N. and Gordon Ritter. "Dynamic Replication and Hedging: A Reinforcement Learning Approach." The Journal of Financial Data Science 1.1 (2019).
Posted: 05 Dec 2018 Last Revised: 16 Mar 2021
Petter N. Kolm and Gordon Ritter
New York University (NYU) - Courant Institute of Mathematical Sciences and New York University (NYU) - Courant Institute of Mathematical Sciences

Abstract:

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Finance; Hedging; Investment analysis; Machine learning; Optimal control; Options; Portfolio optimization; Reinforcement learning