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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, supervised by Professor Oliver Linton. Prior to that, I studied mathematics and statistics at Imperial College London.

My research focuses on the econometric analysis of large-scale time series data. I primarily study nonparametric methods, high-frequency econometrics, and statistical machine learning for the modelling of financial and/or other complex datasets.

• My academic genealogy
• In March 2023, I co-organised a financial econometrics conference in honour of Professor Stephen Taylor.
• In June 2022, I co-organised a workshop on Volatility, Jumps, and Bursts.
• At NTU, I teach MH4519 Financial Econometrics, HE4046 Big Data in Economics and Finance, and HE7002 PhD Econometrics I (50%).

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)
  Revise and Resubmit (R&R), Management Science

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

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

• Volatility Forecasting Factors
  (with Marco Cinquetti, Ingmar Nolte and Sandra Nolte) [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).
  Journal of Financial Econometrics 21, (2023). [Paper]

• 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.
  Journal of Econometrics 219, (2020). [Paper]

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

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

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

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)

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