Research Activities

I. Publications in SOA designated journals:

  1. Lu Xiong, Jiyao Luo, Hanna Vise, Madison White, "Distributed Least-Squares Monte Carlo for American Option Pricing." Risks 11, no. 8 (2023): 145. https://doi.org/10.3390/risks11080145
  2. Vajira Manathunga, Linmiao Deng "Pricing Pandemic Bonds under Hull–White & Stochastic Logistic Growth Model." Risks 11, no. 9 (2023): 155. https://doi.org/10.3390/risks11090155
  3. Lu Xiong, Vajira Manathunga, Jiyao Luo, Nicholas Dennison, Ruicheng Zhang, Zhenhai Xiang, "AutoReserve: A Web-Based Tool for Personal Auto Insurance Loss Reserving with Classical and Machine Learning Methods." Risks 11, no. 7 (2023): 131. https://doi.org/10.3390/risks11070131  
  4. Shuzhe Xu, Chuanlong Zhang, and Don Hong, BERT-based NLP techniques for classification and severity modeling in basic warranty data study, Insurance: Mathematics and Economics, Volume 107, November 2022, Pages 57-67. https://doi.org/10.1016/j.insmatheco.2022.07.013 
  5. Shuzhe Xu, Vajira Manathunga, Don Hong, Framework for BERT Based NLP Models with Applications to Warranty Policy Loss Prediction, 2022,  Variance Journal (accepted). (Available upon request) 

II. Actuarial Science related research published in other journals:

  1. Yu Liu, Lingxuan Yang, Lu Xiong, "Performance commitments and the properties of analyst earnings forecasts: Evidence from Chinese reverse merger firms." International Review of Financial Analysis 89 (2023): 102775. https://doi.org/10.1016/j.irfa.2023.102775 
  2. Lu Xiong and Don Hong 2022. CapSolve: A Solvency Assessment and Prediction Framework for Workers’ Compensation Captive Insurance Companies. Journal of Insurance Issues. 45, 2 (Nov. 2022), 82-113. https://www.jstor.org/stable/48703228 
  3. Vajira Manathunga and Danlei Zhu. "Unearned premium risk and machine learning techniques." Frontiers in Applied Mathematics and Statistics: 118(2022). https://doi.org/10.3389/fams.2022.1056529   
  4. Donglin Wang, Don Hong, and Qiang Wu, Prediction of Loan Rate for Mortgage Data: Deep Learning Versus Robust Regression, Computational Economics, 2022. https://doi.org/10.1007/s10614-022-10239-5 
  5. Chen, Yuan, and Abdul QM Khaliq. "Comparative Study of Mortality Rate Prediction Using Data-Driven Recurrent Neural Networks and the Lee–Carter Model." Big Data and Cognitive Computing 6.4 (2022): 134.  https://doi.org/10.3390/bdcc6040134  
  6. G Tour, N Thakoor, AQM Khaliq, DY Tangman. COS method for option pricing under a regime-switching model with time-changed Lévy processes, Quantitative Finance 2018, 18(4): 673-692. https://doi.org/10.1080/14697688.2017.1412494 
  7. Le Yin, Qiang Wu, and Don Hong. Statistical Methods for Medical Trend Analysis in Health Rate Review Process, Journal of Health & Medical Informatics, 7:219 (2016).  https://doi.org/10.4172/2157-7420.1000219      

III. Other actuarial related research publications:

  1. S. Hansun, F.P. Putri, A.Q.M. Khaliq, H. Hugeng, On searching the best mode for forex forecasting: bidirectional long short-term memory default mode is not enough, IAES International Journal of Artificial Intelligence, 11(4), 1596-1606. 2022. http://doi.org/10.11591/ijai.v11.i4.pp1596-1606 
  2. Seng Hansun, Arya Wickson and Abdul Q. M. Khaliq, Multivariate cryptocurrency prediction: comparative analysis of three recurrent neural networks approaches, Journal of Big Data 9:50, 2022, https://doi.org/10.1186/s40537-022-00601-7 
  3. Lu Xiong, Tingting Sun, and Randall Green. "Predictive analytics for 30-day hospital readmissions." Mathematical Foundations of Computing 5.2 (2022): 93. https://doi.org/10.3934/mfc.2021035
  4. Lu Xiong, Predictive Modeling for Transportation Security Administration Claims Data. ANWESH: International Journal of Management & Information Technology. Volume 7-2(September 2022), 10-20. http://www.publishingindia.com/anwesh/106/predictive-modelling-for-transportation-security-administration-claims-data/32006/76746/ 
  5. Lu Xiong and Williams, S.D., Generalized Linear Model for Predicting the Credit Card Default Payment Risk. Advances in Science, Technology and Engineering Systems Journal. Special Issue on Innovation in Computing, Engineering Science & Technology (May 2022). https://doi.org/10.25046/aj070306 
  6. Lu Xiong, Comparative Study of Predictive Analytics Algorithms and Tools on Property and Casualty Insurance Solvency Prediction. The 4th International Conference on Business and Information Management (Oct. 2020), 81-88. https://doi.org/10.1145/3418653.3418663 
  7.  M Yousuf, AQM Khaliq. Partial differential integral equation model for pricing American option under multi state regime switching with jumps, Numerical Methods for Partial Differential Equations, 2021. https://doi.org/10.1002/num.22791 
  8. M Yousuf, AQM Khaliq, S Alrabeei. Solving complex PIDE systems for pricing American option under multi-state regime switching jump–diffusion model, Computers & Mathematics with Applications, 2018, 75(8): 2989-3001 https://doi.org/10.1016/j.camwa.2018.01.026 
  9.  Harold A. Lay, Zane Colgin, Viktor Reshniak, Abdul Q. M. Khaliq, On the implementation of multilevel Monte Carlo simulation of the stochastic volatility and interest rate model using multi-GPU clusters, Monte Carlo Methods and Applications, 24(4), 309–321, 2018 https://doi.org/10.1515/mcma-2018-2025 

IV. Research grants in Actuarial Science or closely related areas 

  1. “NLP and other AI Techniques for Applications in Actuarial Science” (Don Hong, Vajira Asanka Manathunga, Qiang Wu, Lu Xiong) for $15,000, 2021 individual grant competition, Sponsored by Society of Actuary and Casualty Actuarial Society, 2021-22
  2. “Healthcare data integration based on HL7 technology” (Lu Xiong, PI) for $42,000 Sponsored by MITEM, 2021-23
  3.  "Pandemic Bond Pricing using epidemic compartment models", Manathunga, V. A. (Principal), Deng, L. (Supporting), Sponsored by Office of Research and Sponsored Programs, Middle Tennessee State University, $9,950.00. December 3, 2021 (January 1, 2022 - December 31, 2022).
  4. "Open Educational Resources for Actuarial Science", Manathunga, V. A. (Principal), Pan, H. (Supporting), Spring 2022-only OER Mini-grants, Sponsored by OER Steering Committee at MTSU, Middle Tennessee State University, $3,250.00. November 24, 2021 (January 15, 2022 - March 31, 2022).
  5. "Open Educational Resources for Actuarial Science",Manathunga, V. A. (Pl), Xiong, L. (Pl), Hong, D. (Supporting), Wu, Q. (Supporting). CBAS Open Educational Resources Grant, CBAS, MTSU Amount funded: $3000 Date Submitted: November 18, 2020. 
  6. "Predicting 30-day Hospital Readmission using Machine Learning Techniques," Lu Xiong, Sponsored by FRCAC, Middle Tennessee State University, $6,500.00. April 2019.
  7. Don Hong (PI), State of Tennessee Health Rate Review Project (Cycle-I), Contract with Tennessee Department of Commerce and Insurance, funded by Health and Human Services (HHS), 2011-2012. Awarded Amount: $300,000.
  8. Don Hong (PI), State of Tennessee Health Rate Review Project (Cycle-II), Contract with Tennessee Department of Commerce and Insurance, funded by Health and Human Services (HHS), 2011-2013. Awarded Amount: $440,000.

V. Actuarial Science related presentations:

a. ARC Presentations
  1. Framework for BERT Based NLP Models with Applications to Warranty Policy, by Vajira Manathunga, Shuzhe Xu, the 57th Actuarial Research Conference, 2022.
  2. Data Driving LSTM Method to Predict Mortality under COVID-19 in the United States Based on Deep Learning, by Yuan Chen, Abdul Khaliq, the 57th Actuarial Research Conference, 2022.
  3. Reducing the runtime of Least Squares Monte Carlo in Risk Management, by Lu Xiong, the 56th Actuarial Research Conference, 2021.
  4. Comparative Study of Predictive Analytics Algorithms and Tools on Property & Casualty Insurance Solvency Prediction, by Lu Xiong, the 54th Actuarial Research Conference, 2019.
  5. Modeling HPI price index using HJM approach, by Kushantha Fernando, Vajira Manathunga, 54th Actuarial Research Conference, August 2019 Indianapolis, IN
  6. Practical Applications for Medical Trend Analysis and Health Rating, by Brent Carpenetti, the 50th Actuarial Research Conference, August 5-8, 2015, Toronto, Canada.
  7. Predictive Analytics for Minor League Baseball Pitchers, by Kim Page, the 50th Actuarial Research Conference, August 5-8, 2015, Toronto, Canada.
  8. Using Monte Carlo Simulation to Predict Captive Solvency, by Lu Xiong, The 49th Actuarial Research Conference, July 2014, University of California Santa Barbara, California.
  9. Trend Analysis Algorithms and Applications to Health Rate Review, by Ye (Zoe) Ye, 48th Actuarial Research Conference, July 2013, Temple University, Philadelphia, PA.
b. Other Presentations
  1. CAS University Award report on MTSU Actuarial Science Program, by Don Hong, the CAS Annual Meeting, Remote, October 2020.
  2. Using Monte Carlo Simulation to Predict Captive Insurance Solvency, by Lu Xiong, Don Hong, the 4th International Conference on Compute and Data Analysis, 2020.
  3. Challenges and Successes of Launching a New Actuarial Science Program, by Haseeb A. Kazi, Vajira Manathunga and Jennifer Yantz, Actuarial Teaching Conference, June 2019, Columbus, OH
  4. American Option Pricing under additive and multiplicative models using HJM approach, by Kushantha Fernando and Vajira Manathunga, 2019 International Workshop on Actuarial Science and Finance, November 29-30, 2019, Ningbo University, China.
  5. Statistical Learning and Predictive Analytics with Applications in Actuarial Science, by Don Hong, Invited talk at 2018 International Workshop on Actuarial Science and Mathematical Finance, Ningbo.

VI. Graduate Student Thesis/Dissertation:

  1. Shuzhe Xu (Dissertation Supervisors: Drs. Don Hong & Sal Barbosa), Ph.D. Dissertation: Applications of Modern NLP Techniques for Predictive Modeling in Actuarial Science. October 2021.
  2. Chuanlong Zhang(Thesis Supervisor: Dr. Don Hong), MS Thesis: Aggregate Loss Prediction Using Multiple-class Classification Techniques, Middle Tennessee State University, Murfreesboro, TN, June 2021.
  3. Yi Xu(Thesis Supervisor: Dr. Yeqian Liu), MS Thesis: Propensity Score Methods for comparing the effect of RHC on survival time, Middle Tennessee State University, Murfreesboro, TN, August 2020.
  4. Ye Fang(Thesis Supervisor: Dr. Don Hong), MS graduate Thesis: PREDICTIVE MODELS FOR AIR SHOW TICKET SALES, Middle Tennessee State University, Murfreesboro, TN, May 2018.
  5. David Matthews(Thesis Supervisor: Dr. Don Hong), MS Thesis: Data Mining and Machine Learning Algorithms for Workers’ Compensation Early Severity Prediction, Middle Tennessee State University, Murfreesboro, TN, May 2016.
  6. Xiong Lu(Dissertation Supervisor: Dr. Don Hong), Ph.D. Dissertation Chapter 3: Statistical Computing Tools for Predicting Captive Solvency, December 2014.
  7. Ye (Zoe) Ye(Theis Supervisor: Dr. Qiang Wu), MS graduate thesis: Tail Conditional Expectations for Extended Dispersion Models, Middle Tennessee State University, Murfreesboro, TN, August 2014.
  8. Le Yin(Thesis Supervisor: Dr. Qiang Wu), MS graduate thesis: Medical Trend Analysis Methods, Middle Tennessee State University, Murfreesboro, TN, May 2014.

VII. Funded Undergraduate Research:  

  1. Xintong Cao, Pengyu Zhu, Minyuan Zhao, Grant Proposal: "Tree-based Machine Learning Algorithms for Analytics of Online Shopper’s Purchasing Intention", Faculty Mentor: Dr. Lu Xiong, Submitted for Spring 2023 MTSU URECA grant. Awarded with $3000.
  2. Zihan Zhang, Yuqi Duan, Grant proposal: “Actuarial Modeling for Medical Loss Prediction and Trend Analysis”; Faculty Mentor: Dr. Don Hong, Dr. Shuzhe Xu; Submitted for Fall 2022 MTSU URECA research grant application. Awarded with $2000.
  3. Xinpeng Hua, Grand Project: “Investigating two parameter composite models and their applications in actuarial science”, Faculty Mentor: Vajira Manathunga; Submitted for Spring 2022 MTSU URECA applications. Awarded with $1000.
  4. Jialin Zhang, Grand Project: “Application of Machine Learning Techniques for Insurance Fraud Detection”, Faculty Mentor: Don Hong; Submitted for Spring 2022 MTSU URECA applications. Awarded with $1000.

VIII. Student Presentations:

  1. Poster Presentation at MTSU 2022 Scholar Week: Tingting Sun, Distributed Regression Version of Least Squares Monte Carlo Algorithm with Map-Reduce and GPU acceleration, March 2022.
  2. Poster Presentation at MTSU 2020 Scholar Week: Jialing Zhang, Application of Machine Learning Techniques for Insurance Fraud Detection, March 2020
  3. Poster Presentation at MTSU 2020 Scholar Week: Tingting Sun, Using the automated machine learning to predict 30-day Hospital Readmission, March 2020.
  4. Poster Presentation at MTSU 2018 Scholar Week: Chuanlong Zhang, Research about Loss Reserving Method in P&C Insurance, March 2018.