Justin Sirignano

Imperial College London - Department of Mathematics

South Kensington Campus

Imperial College

LONDON, SW7 2AZ

United Kingdom

http://jasirign.github.io

University of Illinois at Urbana-Champaign

601 E John St

Champaign, IL 61820

United States

SCHOLARLY PAPERS

9

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CITATIONS
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Top 17,013

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41

Scholarly Papers (9)

1.

Deep Learning for Mortgage Risk

Number of pages: 75 Posted: 23 Jun 2016 Last Revised: 22 Nov 2018
Justin Sirignano, Apaar Sadhwani and Kay Giesecke
Imperial College London - Department of Mathematics, Stanford University and Stanford University - Management Science & Engineering
Downloads 3,769 (2,438)
Citation 14

Abstract:

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Deep Learning, Machine Learning, Mortgages, Loans, Credit Risk, Prepayment Risk, Nonlinear Model

2.

Universal Features of Price Formation in Financial Markets: Perspectives From Deep Learning

Number of pages: 20 Posted: 16 Mar 2018 Last Revised: 29 Mar 2018
Justin Sirignano and Rama Cont
Imperial College London - Department of Mathematics and University of Oxford
Downloads 3,015 (3,574)
Citation 7

Abstract:

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Financial Econometrics, High Frequency Data, Machine Learning, Deep Learning, Price Formation, Market Microstructure, Intraday Data, Limit Order Book

3.

Deep Learning for Limit Order Books

Number of pages: 39 Posted: 04 Jan 2016 Last Revised: 11 Jan 2017
Justin Sirignano
Imperial College London - Department of Mathematics
Downloads 1,703 (9,374)
Citation 1

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neural network, machine learning, deep learning, limit order book, high frequency trading

4.

Large-Scale Loan Portfolio Selection

Operations Research, 64, 1239-1255, 2016
Number of pages: 41 Posted: 08 Aug 2015 Last Revised: 03 Aug 2017
Justin Sirignano, Gerry Tsoukalas and Kay Giesecke
Imperial College London - Department of Mathematics, University of Pennsylvania - The Wharton School and Stanford University - Management Science & Engineering
Downloads 744 (32,627)
Citation 2

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loan portfolio optimization, loan, mortgage, loan portfolio, portfolio optimization, default, prepayment, machine learning, law of large numbers, central limit theorem

5.

Risk Analysis for Large Pools of Loans

Number of pages: 62 Posted: 24 Oct 2014 Last Revised: 06 Sep 2017
Justin Sirignano and Kay Giesecke
Imperial College London - Department of Mathematics and Stanford University - Management Science & Engineering
Downloads 402 (71,857)
Citation 1

Abstract:

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Loans, loan default, default risk, prepayment risk, loan prepayment, loan risk, mortgages, mortgage-backed security, asset-backed security, mortgage default, mortgage prepayment, large pools, law of large numbers, central limit theorem, data-driven models, machine learning

6.

Stochastic Gradient Descent in Continuous Time

Number of pages: 24 Posted: 20 Apr 2017
Justin Sirignano and Konstantinos Spiliopoulos
Imperial College London - Department of Mathematics and Brown University - Division of Applied Mathematics
Downloads 126 (223,315)
Citation 2

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Statistical Learning, Machine Learning, Finance, American Options, Financial Engineering, Financial Math

7.

Inference for Large Financial Systems

Boston University Questrom School of Business Research Paper
Number of pages: 56 Posted: 04 Aug 2017 Last Revised: 09 Jan 2019
Kay Giesecke, Gustavo Schwenkler and Justin Sirignano
Stanford University - Management Science & Engineering, Boston University - Questrom School of Business and Imperial College London - Department of Mathematics
Downloads 118 (234,635)
Citation 1

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Interacting stochastic systems, likelihood inference, weak limits, large system asymptotics, indirect inference

8.
Downloads 118 (234,635)
Citation 14

Large Portfolio Asymptotics for Loss from Default

Mathematical Finance, Forthcoming
Number of pages: 29 Posted: 06 Sep 2011 Last Revised: 18 Oct 2013
Stanford University - Management Science & Engineering, Brown University - Division of Applied Mathematics, University of Illinois at Urbana-Champaign - Department of Mathematics and Imperial College London - Department of Mathematics
Downloads 118 (235,697)
Citation 2

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law of large numbers, loss distribution, interacting point processes, portfolio credit risk

Large Portfolio Asymptotics for Loss from Default

Mathematical Finance, Vol. 25, Issue 1, pp. 77-114, 2015
Number of pages: 38 Posted: 17 Jan 2015
Kay Giesecke, Richard Sowers and Justin Sirignano
Stanford University - Management Science & Engineering, University of Illinois at Urbana-Champaign - Department of Mathematics and Imperial College London - Department of Mathematics
Downloads 0
Citation 1
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law of large numbers, interacting point process, credit risk

9.

Fluctuation Analysis for the Loss from Default

Number of pages: 32 Posted: 03 Mar 2013 Last Revised: 06 Feb 2014
Konstantinos Spiliopoulos, Justin Sirignano and Kay Giesecke
Brown University - Division of Applied Mathematics, Imperial College London - Department of Mathematics and Stanford University - Management Science & Engineering
Downloads 96 (270,603)

Abstract:

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CLT, fluctuations analysis, portfolio loss, risk management, approximation