Research

Research Interests: Time Series Analysis and Forecasting

• Univariate or Multivariate ARIMA(X) Models, Cointegration Analysis

• Univariate or Multivariate Exponential Smoothing Models

• Mixed-Frequency Time Series Analysis

• Automatic Forecasting, Hybrid or Combinational Forecasting, Hierarchical Forecasting

• Intervention Analysis

• Count Time Series Models

• Hidden Markov Models, Dynamic Linear Models and State Space Models

Projects

• A study on advanced exponential smoothing models, NRF2022

• A study on hidden Markov models for dynamic time series analysis , NRF2020

• A study on exponential smoothing models with mixed-frequency time series data, NRF2016

• A study on cointegration in high-dimensional time series data , KRF2012

• A study on nonstandard tests for cointegration, KRF2009

• Joint modeling for heteroscedastic cointegration and its extensions , KRF2007

• Joint modeling of cointegration and conditional heteroscedasticity , KRF2006

• Seasonal cointegration and its extensions, KOSEF2004

Publications

1. Kim, S. and Seong, B. (11/2022). “Grouping Stocks Using Dynamic Linear Models,” Communications for Statistical Applications and Methods, 29(6), 695-708.

2. Oh, J. and Seong, B. (10/2022). “Performance Comparison for Automatic Forecasting Functions in R,” The Korean Journal of Applied Statistics, 35(5), 645-655.

3. Kim, S., Seong, B., Choi, Y. and Yeo, I. (08/2022). “A Study on Time Series Linkage in the Household Income and Expenditure Survey,” The Korean Journal of Applied Statistics, 35(4), 553-568.

4. Lee, S. and Seong, B. (06/2022). “Performance for Simple Combinations of Univariate Forecasting Models,” The Korean Journal of Applied Statistics, 35(3), 385-393.

5. Seong, B. and Lee, K. (05/2021). “Intervention Analysis Based on Exponential Smoothing Methods: Applications to 9/11 and COVID-19 Effects,” Economic Modelling, 98, 290-301.

6. Jin, J., and Seong, B. (12/2020). “Analysis of the Differences in Living Population Changes and Regional Responses by COVID-19 Outbreak in Seoul,” The Korean Journal of Applied Statistics, 33(6), 697-712.

7. Seong, B. (09/2020). “Smoothing and Forecasting Mixed-Frequency Time Series with Vector Exponential Smoothing Models,” Economic Modelling, 91, 463-468.

8. Lee, Y., and Seong, B. (06/2020). “Multivariate Exponential Smoothing Models with Application to Exchange Rates,” The Korean Journal of Applied Statistics, 33(3), 257-267.

9. Ji, Y., and Seong, B. (04/2020). “Automatic Order Selection Procedure for Count Time Series Models,” The Korean Journal of Applied Statistics, 33(2), 147-160.

10. Bae, D., and Seong, B. (12/2019). “Multiple Aggregation Prediction Algorithm Applied to Traffic Accident Counts,” The Korean Journal of Applied Statistics, 32(6), 851-865.

11. Park, M., Lim, M., and Seong, B. (04/2018), “Forecasting Drug Expenditure with Transfer Function Model,” The Korean Journal of Applied Statistics, 31(2), 303-313.

12. Jun, G., and Seong, B. (04/2018), “Temporal Hierarchical Forecasting with an Application to Traffic Accident Counts,” The Korean Journal of Applied Statistics, 31(2), 229−239.

13. Song, Y., and Seong, B. (10/2017), “Effects of Maximum Speed Limit on Gyeongbu Expressway,” The Korean Journal of Applied Statistics, 30(5), 719−731.

14. Lee, J., and Seong, B. (02/2017), “Hierarchical Time Series Forecasting with an Application to Traffic Accident Counts,” The Korean Journal of Applied Statistics, 30(1), 181−193.

15. Won, J., Chang, I., and Seong, B. (06/2016), “An Application of ARIMAX for Predicting Long-Term National Health Insurance Expenditure in Korea,” The Korean Journal of Health Economics and Policy, 22(2), 1-27.

16. Won, D., and Seong, B. (06/2016), “Electricity Demand Forecasting Based on Innovations State Space Exponential Smoothing Models,” The Korean Journal of Applied Statistics, 29(4), 581−594.

17. Kim, H., and Seong, B. (04/2016), “EMD Based Hybrid Models for Forecasting KOSPI,” The Korean Journal of Applied Statistics, 29(3), 525−537.

18. Lee, J., and Seong, B. (02/2016), “A study on parsimonious periodic autoregressive model,” The Korean Journal of Applied Statistics, 29(1), 133−144.

19. Seong, B. (11/2015), “Estimation of seasonal cointegration under conditional heteroskedasticity,” Communications for Statistical Applications and Methods, 22(6), 615−624.

20. Lee, J., and Seong, B. (10/2015), “Performance Comparison of Estimation Methods for Dynamic Conditional Correlation,” The Korean Journal of Applied Statistics, 28(5), 1013−1024.

21. Seong, B. (09/2015), “A simple GLS procedure for seasonal cointegration,” Journal of the Korean Statistical Society, 44(3), 469−476.

22. Hao, N., Colson, G., Seong, B., Park, C., and Wetzstein, M. (05/2015), ”Drought, ethanol, and livestock,” Energy Economics, 49, 301−307.

23. Huh, J., and Seong, B. (06/2015), “Volatility forecasting of Korea composite stock price index with MRS-GARCH model,” The Korean Journal of Applied Statistics, 28(3), 429−442.

24. Park, M. and Seong, B. (06/2014), “Comparison of EMD and HP filter for cycle extraction with Korean macroeconomic indices,” The Korean Journal of Applied Statistics, 27(3), 431−444.

25. Seong, B. and Jung, H. (12/2013), “Structural vector error correction model for Korean labor market data,” The Korean Journal of Applied Statistics, 26(6), 1043−1051.

26. Seong, B. (09/2013), “Semiparametric selection of seasonal cointegrating ranks using information criteria,” Economics Letters, 120(3), 592−595.

27. Seong, B., Ahn, S. K., and Zadrozny, P. A. (03/2013), “Estimation of vector error correction models with mixed-frequency data,” Journal of Time Series Analysis, 34(2), 194−205.

28. Seong, B. (2013), “Bootstrap test for seasonal cointegrating ranks,” Applied Economics Letters, 20(2), 147−151.

29. Seong, B. (12/2012), “Cointegration Analysis with Mixed-Frequency Data of Quarterly GDP and Monthly Coincident Indicators,“ The Korean Journal of Applied Statistics, 25(6), 925−932.

30. Seong, B., Ahn, S. K., and Cho, S. (10/2011), “Semiparametric Seasonal Cointegrating Rank Selection,” The Korean Journal of Applied Statistics, 24(5), 791−797.

31. Kim, S., and Seong, B. (10/2011), "Intervention Analysis of Korea Tourism Data," The Korean Journal of Applied Statistics, 24(5), 735−743.

32. Seong, B., and Lee, S. (09/2011), ”Analysis of Korean GDP by unobserved components model,” Journal of the Korean Data and Information Science Society, 22(5), 829−837.

33. Park, S. K., Cho, S., and Seong, B. (04/2011), “GMM Estimation for Seasonal Cointegration,” The Korean Journal of Applied Statistics, 24(2), 227−237.

34. Seong, B. (01/2011), “Comparison of Forecasting Performance in Multivariate Nonstationary Seasonal Time Series Models,” Communications of the Korean Statistical Society, 18(1), 13−21.

35. Kang, S., Lee, S., Won, Y., and Seong, B. (03/2010), “On-Line Prediction of Nonstationary Variable-Bit-Rate Video Traffic,” IEEE Transactions on Signal Processing, 58(3), 1219−1237.

36. Seong, B. (06/2009), “Extended Complex Error Correction Models for Seasonal Cointegration,” Journal of the Korean Statistical Society, 38(2), 191−198.

37. Seong, B. (04/2009), “Bonferroni Correction for Seasonal Cointegrating Ranks,” Economics Letters, 103(1), 42−44.

38. Seong, B., Cho, S., Ahn, S. K., and Hwang, S. Y. (10/2008), “Effects of the Misspecification of Cointegrating Ranks in Seasonal Models,” The Korean Journal of Applied Statistics, 21(5), 783−789.

39. Seong, B., Ahn, S. K., and Jeon, Y. (09/2008), “A Note on Spurious Regression in Seasonal Time Series,” Journal of Statistical Computation and Simulation, 78(9), 843−851.

40. Seong, B., and Yi, Y. J. (09/2008), “Joint Test for Seasonal Cointegrating Ranks,” Communications of the Korean Statistical Society, 15(5), 719−726.

41. Seong, B. (05/2008), “A Feasible Two-Step Estimator for Seasonal Cointegration,” Communications of the Korean Statistical Society, 15(3), 411−420.

42. Seong, B., Cho, S., and Ahn, S. K. (07/2007), “Inference of Seasonal Cointegration with Linear Restrictions,” Journal of Statistical Computation and Simulation, 77(7), 593−603.

43. Kang, S., Won, Y., and Seong, B. (06/2007), “On-line Prediction Algorithm for Non-stationary VBR Traffic,” Journal of KISS: Information Networking, 34(3), 156−167.

44. Seong, B., Morshedb, A. M., and Ahn, S. K. (12/2006), “Additional Sources of Bias in Half-life Estimation,” Computational Statistics and Data Analysis, 51(3), 2056−2064.

45. Seong, B., Cho, S., and Ahn, S. K. (08/2006), “Maximum Eigenvalue Test for Seasonal Cointegrating Ranks,” Oxford Bulletin of Economics and Statistics, 68(4), 497−514.

46. Ahn, S. K., Cho, S., and Seong, B. C. (05/2004), “Inference of Seasonal Cointegration: Gaussian Reduced Rank Estimation and Tests for Various Types of Cointegration,” Oxford Bulletin of Economics and Statistics, 66(2), 261−284.

47. Cho, S., Song, M., Lee, Y., Seong, B., Yoon, Y., and Lee, H. (06/1999), “Development of Statistical Software for the Education of Statistics at the Introductory Level based on Excel,” Journal of the Korean Society for Quality Management, 27(2), 277−290.