Liang Hong

The University of Texas at Dallas

Associate Professor

2601 North Floyd Road

Richardson, TX 75083

United States

SCHOLARLY PAPERS

21

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1,124

SSRN CITATIONS
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Top 22,878

in Total Papers Citations

36

CROSSREF CITATIONS

4

Scholarly Papers (21)

1.

A Flexible Bayesian Nonparametric Model for Predicting Future Insurance Claims

Number of pages: 21 Posted: 16 Nov 2015 Last Revised: 05 Nov 2016
Liang Hong and Ryan Martin
The University of Texas at Dallas and North Carolina State University - Department of Statistics
Downloads 186 (182,822)
Citation 3

Abstract:

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Credibility theory; density estimation; Dirichlet process; Markov chain Monte Carlo; mixture model; posterior consistency.

2.

On Prediction of Future Insurance Claims When the Model Is Uncertain

Number of pages: 13 Posted: 12 Dec 2016 Last Revised: 22 Feb 2017
Liang Hong, Todd Kuffner and Ryan Martin
The University of Texas at Dallas, Washington University in St. Louis and North Carolina State University - Department of Statistics
Downloads 157 (211,683)
Citation 3

Abstract:

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Bootstrap; Post-Selection Inference; Predictive Distribution; Regression; Variable Selection

3.

Dirichlet Process Mixture Models for Insurance Loss Data

Number of pages: 13 Posted: 11 Apr 2017 Last Revised: 31 Oct 2017
Liang Hong and Ryan Martin
The University of Texas at Dallas and North Carolina State University - Department of Statistics
Downloads 106 (285,750)
Citation 2

Abstract:

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Danish Fire Losses Data; General Insurance; Model Misspecification; Nonparametric Bayes; Norwegian Fire Losses Data; Property and Casualty Insurance; U.S. Allocated Loss Adjustment Expenses Data

4.

A Review of Bayesian Asymptotics in General Insurance Applications

Number of pages: 26 Posted: 03 Mar 2016 Last Revised: 08 Apr 2017
Liang Hong and Ryan Martin
The University of Texas at Dallas and North Carolina State University - Department of Statistics
Downloads 104 (289,584)
Citation 2

Abstract:

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General insurance; nonparametric Bayes; posterior consistency; posterior robustness; property and casualty insurance

5.

Real-Time Bayesian Nonparametric Prediction of Solvency Risk

Number of pages: 16 Posted: 13 Jun 2017 Last Revised: 10 Dec 2017
Liang Hong and Ryan Martin
The University of Texas at Dallas and North Carolina State University - Department of Statistics
Downloads 79 (344,244)
Citation 1

Abstract:

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density estimation; mixture model; nonparametric Bayes; risk management; value-at-risk; conditonal tail expectation.

6.

Whoops! It Happened Again. Demand for Insurance that Covers Multiple Risks

Number of pages: 25 Posted: 18 Apr 2016 Last Revised: 22 Sep 2020
The University of Texas at Dallas, University of Alabama and The University of Alabama - ACIIR
Downloads 77 (349,347)
Citation 1

Abstract:

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Two-period Model; Insurance; Multiple Risks; Riskiness.

7.

Model Misspecification, Bayesian Versus Credibility Estimation, and Gibbs Posteriors

Number of pages: 22 Posted: 18 Jul 2019 Last Revised: 21 Nov 2019
Liang Hong and Ryan Martin
The University of Texas at Dallas and North Carolina State University - Department of Statistics
Downloads 51 (430,236)
Citation 2

Abstract:

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asymptotics; Bernstein--von Mises phenomenon; exponential family; robustness; uncertainty quantification

8.

On the Choice between Two Delta-Hedging Strategies

Number of pages: 16 Posted: 16 Nov 2015
Liang Hong
The University of Texas at Dallas
Downloads 49 (437,736)

Abstract:

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Cost of hedging, Re-balancing, Markov chain, Random walk, Fixed transaction cost, Non-fixed transaction cost.

9.

Valid Model-Free Prediction of Future Insurance Claims

Number of pages: 18 Posted: 22 Oct 2019 Last Revised: 26 Feb 2020
Liang Hong and Ryan Martin
The University of Texas at Dallas and North Carolina State University - Department of Statistics
Downloads 46 (449,254)

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Machine learning; model misspecification; predictive modeling; robustness; unsupervised learning.

10.

Discussion on Credibility Estimation of Distribution Functions with Applications to Experience Rating in General Insurance

North American Actuarial Journal, 2016, Forthcoming
Number of pages: 6 Posted: 15 Jan 2016
Liang Hong and Ryan Martin
The University of Texas at Dallas and North Carolina State University - Department of Statistics
Downloads 39 (478,738)
Citation 4

Abstract:

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11.

On the Properties of the Primary Loss and the Excess Loss in NCCI's Experience Rating Plan

Number of pages: 31 Posted: 16 Nov 2015 Last Revised: 26 Oct 2017
Liang Hong
The University of Texas at Dallas
Downloads 37 (487,725)

Abstract:

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Workers compensation, credibility theory, split point, state limit, coefficient of variation, total loss, covariance, correlation coefficient, collective risk model

12.

Gibbs Posterior Inference on Value-at-Risk

Number of pages: 13 Posted: 20 Sep 2018
Nicholas Syring, Liang Hong and Ryan Martin
Department of Mathematics, The University of Texas at Dallas and North Carolina State University - Department of Statistics
Downloads 27 (539,023)
Citation 2

Abstract:

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13.

A Further Study of the Choice between Two Hedging Strategies - The Continuous Case

Number of pages: 14 Posted: 11 Apr 2016 Last Revised: 30 Oct 2017
Liang Hong
The University of Texas at Dallas
Downloads 25 (551,050)

Abstract:

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Cost of hedging; continuous-time Markov process; first hitting time; Brownian motion with drift; fixed transaction cost; non-fixed transaction cost

14.

Discussion on 'q-Credibility' by Olivier Le Courtois

Number of pages: 6 Posted: 16 Dec 2018 Last Revised: 28 Mar 2019
Liang Hong and Ryan Martin
The University of Texas at Dallas and North Carolina State University - Department of Statistics
Downloads 24 (557,303)
Citation 1

Abstract:

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credibility, Bayesian, nonparametric statistics

15.

On Three Standard Results in the Theory of Insurance Demand

Number of pages: 20 Posted: 13 Aug 2018 Last Revised: 27 Mar 2019
Liang Hong
The University of Texas at Dallas
Downloads 23 (563,576)
Citation 2

Abstract:

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optimal insurance level; coinsurance; deductible insurance; upper-limit insurance; changes in initial wealth; changes in price; unified framework

16.

Mossin's Theorem Without the Expected-Utility Framework

Number of pages: 18 Posted: 19 Oct 2018 Last Revised: 19 Aug 2019
Liang Hong
The University of Texas at Dallas
Downloads 21 (576,396)

Abstract:

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optimal insurance demand; non-expected-utility framework; robustness; coinsurance; deductible insurance; upper-limit insurance

17.

Some Remarks on the Mossin Theorem

Number of pages: 22 Posted: 23 Aug 2017 Last Revised: 19 May 2018
Liang Hong
The University of Texas at Dallas
Downloads 19 (589,657)
Citation 3

Abstract:

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Coinsurance; Deductible insurance; Upper-limit insurance; Random initial wealth; Expectation dependence; Quadrant dependence; Regression dependence; Arbitrary distribution

18.

Optimal Insurance Coverage With Default Risk

Number of pages: 15 Posted: 01 May 2019 Last Revised: 21 Aug 2020
Liang Hong, Zhiqiang Yan and Boyi Zhuang
The University of Texas at Dallas, Western Illinois University - Department of Marketing and Finance and The University of Alabama - ACIIR
Downloads 17 (602,730)

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Mossin's Theorem; total default; partial default; coinsurance; deductible insurance; upper-limit insurance

19.

Imprecise Credibility Theory

Number of pages: 19 Posted: 20 Nov 2020
Liang Hong and Ryan Martin
The University of Texas at Dallas and North Carolina State University - Department of Statistics
Downloads 14 (623,148)

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Imprecise probability; credibility estimator; model misspecification; prior uncertainty; robustness

20.

A Note on Mossin's Theorem for Deductible Insurance Given Random Initial Wealth

Number of pages: 18 Posted: 24 Jul 2017 Last Revised: 17 Aug 2017
Liang Hong
The University of Texas at Dallas
Downloads 14 (623,148)
Citation 3

Abstract:

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Deductible insurance; Random initial wealth; Expectation dependence; Quadrant dependence; Regression dependence

21.

Sample Size Determination for Credibility Estimation

Number of pages: 15 Posted: 20 Nov 2020
Liang Hong
The University of Texas at Dallas
Downloads 9 (658,935)

Abstract:

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Bayesian analysis; credibility theory; experience rating; predictive modeling; sample size criterion