s.y.hong [at] lancaster.ac.uk
Lancaster University Management School
Bailrigg, Lancaster LA1 4YX, United Kingdom
I am an Associate Professor at Lancaster University Management School.
Before joining Lancaster I worked at Nottingham University as an Assistant Professor.
Previously, I was at Cambridge University where I completed Mathematical Tripos Part III and then
a PhD in Pure Mathematics and Mathematical Statistics in 2018, supervised by Prof. Oliver Linton.
My primary research interests lie on developing time series methods for economic/financial applications.
** This March I am co-orgnising a financial econometrics conference in honour of Professor Stephen Taylor, conference link.
** In June 2022 I co-organised a workshop on Volatility, Jumps and Bursts.
Some Working Papers
• Comparing factor models with conditioning information
(with Shamim Ahmed and Daniel Tsvetanov). Submitted & Under Review
• Separate noise and jumps from tick data:
an easy-to-adopt endogenous thresholding approach
(with Xiaolu Zhao and Oliver Linton).
• On the suitability of mixing-type conditions: are they really appropriate for economic data?
• Volatility estimation and forecasts using price durations
(with Ingmar Nolte, Stephen J. Taylor and Xiaolu Zhao).
Journal of Financial Econometrics 21, (2023). [Paper Link]
• 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 Link]
• 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.
Journal of Financial Econometrics 15, (2017). [Paper Link]
• 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 Link]
• Small Deviations in L2-norm for Gaussian Dependent Sequences
(with Mikhail Lifshits and Alexander Nazarov).
Electronic Communications in Probability 21, (2016). [Paper Link]
Teaching – All materials are available on Moodle
From Year 2019:
⁃ Topics in Advanced Econometrics II (PhD)
⁃ Econometric Topics in Accounting and Finance (PhD)
⁃ Financial Stochastic Processes (MSc)
⁃ Research Methods for Risk Management (MSc)
⁃ Introduction to Quantitative Methods (MSc)
⁃ Foundations of Financial Markets (BSc/MSc)
⁃ Derivative Pricing (MSc)