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Seok Young Hong

CV:  pdf

seokyoung.hong [at] ntu.edu.sg

I am an Assistant Professor of Economics and Data Science at Nanyang Technological University, Singapore.

I studied at the University of Cambridge where I completed the Mathematical Tripos Part III and then earned a PhD in Mathematics in 2018 (Advisor: Oliver Linton; my academic genealogy). Prior to that, I studied mathematics and statistics at Imperial College London.

My research focuses on the econometric analysis of large-scale time series.
I primarily study nonparametric methods, high-frequency econometrics, and statistical machine learning for the modelling of financial data.
At NTU, I currently teach MH4519 Financial Econometrics, HE4046 Big Data in Economics and Finance, and HE7002 PhD Econometrics I.

Research Papers

• Fully Unsupervised Learning for Anomaly Detection with Noisy Training Data
  (with Jehyeong Hong et al.) [Paper] (2026)

• Jumps versus bursts: distinguishing sources of extreme risk in financial markets
  (with Xiaolu Zhao and Oliver Linton) [Paper] (2026)
  R&R at Management Science

• Volatility Forecasting Factors
  (with Marco Cinquetti, Ingmar Nolte and Sandra Nolte) [Paper] (2026)
  R&R at Journal of Business & Economic Statistics

• Unified Inference for Predictive Mean and Quantile Regressions via Empirical Likelihood
  (with Zongwu Cai, Yifeng Chen and Daniel Tsvetanov) [Paper] (2026)
  R&R at Journal of Econometrics

• Regular and reverse Midastar models: Threshold autoregression with mixed frequency data
  (with Kaiji Motegi and John Dennis) [Paper] (2026)

• PINGS-X: Physics-Informed Normalized Gaussian Splatting with Axes Alignment
  (with Sun Jo, Jehyeong Hong et al.; co-first author) [Paper] [Python Code]
  Proceedings of the Association for the Advancement of Artificial Intelligence (AAAI) 40(7), (2026)

• Volatility estimation and forecasts based on price durations
  (with Ingmar Nolte, Stephen J. Taylor and Xiaolu Zhao). [Paper]
  Journal of Financial Econometrics 21, (2023).

• Nonparametric estimation of infinite order regression and its application to the risk-return tradeoff
  (with Oliver Linton). Awarded the Smith/Rayleigh-Knight Prize on an earlier version. [Paper]
  Journal of Econometrics 219, (2020)

• Estimating the Quadratic Covariation Matrix for Asynchronously observed high frequency stock returns corrupted
   by Additive Measurement Error (with Sujin Park and Oliver Linton). [Paper]
  Journal of Econometrics 191, (2016)

• An Investigation into Multivariate Variance Ratio Statistics and Their Application to Stock Market Predictability
  (with Hui Jun Zhang and Oliver Linton). Halbert White Jr. Memorial Invited Paper. [Paper]
  Journal of Financial Econometrics 15, (2017)

• Small Deviations in L2-norm for Gaussian Dependent Sequences
  (with Mikhail Lifshits and Alexander Nazarov). [Paper]
  Electronic Communications in Probability 21, (2016).


Teaching

I have taught the following modules:

⁃ Econometrics I (PhD; NTU)
⁃ Topics in Advanced Econometrics II (PhD; Nottingham)
⁃ Econometric Topics in Accounting and Finance (PhD; Lancaster)
⁃ Financial Stochastic Processes (MSc; Lancaster)
⁃ Research Methods for Risk Management (MSc; Nottingham)
⁃ Introduction to Quantitative Methods (MSc; Lancaster)
⁃ Foundations of Financial Markets (UG/MSc; Lancaster)
⁃ Derivative Pricing (MSc; Lancaster)
⁃ Financial Econometrics (UG; NTU Singapore)
⁃ Big Data in Economics and Finance (UG; NTU Singapore)
⁃ Mathematics/Statistics for Economists (UG; Cambridge)



Last Updated: June 2026