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Time series econometrics  

Sparse Bayesian Learning

Wavelet methods

Statistical machine learning 

Statistical Surveillance

Lecturer and course responsible:

STAT250(V22 Cooperate with ):Monte Carlo Methods and Bayesian Statistics

STAT260(H20,H21,H23)/STATLEARN(H17,H18, H19): Statistical learning 

STAT240 (V17,V21,V23), UIB: Theory of Finance

STAT231 (H16,H20,H22,H24), UIB: Nonlife insurance mathematics

STAT111 (V16, V18), UIB: Statistiske metoder (Bachelor level. Given in Norwegian)

STAT250 (H15), UIB: Monte Carlo methods in statistics

ECO403 (V15,V14), NHH:

MAT013 (H14), NHH:Matematisk statistikk (Bachelor level. Given in Norwegian)

External grading sensor (2017-):

ENE473 Real Options Analysis of Electricity Markets, NHH 

BEA525 Financial Engineering in Energy Markets using Real Options, NHH

GRA 4136/41363 Predictive Analytics and Machine Learning/ Machine Learning for Business, BI OSLO

TMA4268 Statistisk læring, NTNU

TMA4900  Industriell matematikk /Datateknologi, masteroppgave, NTNU

IT3920/3903  Masteroppgave for MSIT/ Masteroppgave i informatikk: Kunstig intelligens, NTNU

Supervised Ph.D. project:

(June 2023, UIB)  Ingvild M. Helgøy, 

Supervised Master projects:

(V12 Lund University) Simon Reese: , Co-supervisor: Fredrik N G Andersson

(V15 NHH) Midtdal S. Tollefsen &  Hans Thomas: "" , Co-supervisor: Ola Honningdal Grytten

(V18 UIB) Therese Grindheim:

(H18 UIB) Victoria Foster: Empirical time series analysis with focus on wavelet methods and economic data from Norway

(V19 UIB) Francine D. D. Rogowski: A Comprehensive Study of Kernels and Feature Selection in Support Vector Regression, Co-supervisor: Bjørn Gunnar Hansen

(H19 UIB) Fredrik H. Bentsen: 

(V20 UIB) Elise F.F. Isaksen:  Generative and Discriminative Classifiers: from Theory to Implementation

(V21 UIB) Sandra Heimsæter: , Co-supervisor: Ingvild M. Helgøy

(V21 UIB) Arne L. Waagbø: 

(V23 UIB) Mathias E. Ostnes: ,Co-supervisor: Ingvild M. Helgøy

2017-2022: 6 bachelor thesis (STAT292 UIB Project in Statistics)

• Hyunjoo Kim Karlsson , Yushu Li (2026) 
  •  Investigation of Swedish Krona exchange rate volatility using APARCH-Support Vector Regression. , Volume 12, article number 7
• Ingvild M. Helgøy, Hans J. Skaug, Yushu Li (2024)
  • Sparse Bayesian learning using TMB (Template Model Builder), , Volume 34, article number 173, Springer
• Bjørn Gunnar Hansen, Yushu Li, Ruohao Sun, Ingunn Schei (2024)
  • Forecasting milk delivery to dairy – How modern statistical and machine learning methods can contribute, (on line 15 Feb.2024), , Elsevier
• Ingvild M. Helgøy and Yushu Li (2023)
  • A Bayesian Lasso based Sparse Learning Model. (Online, 26 Oct 2023), 
    , Taylor & Francis
• Yushu Li and Hyunjoo Kim Karlsson (2022)
  • Investigating the Asymmetric Behavior of Oil Price Volatility Using Support Vector Regression,  (Online, May 6, 2022), , Springer
• Yushu Li and Fredrik N.G. Andersson (2021)
  • A simple wavelet-based test for serial correlation in panel data models, , 60, pp. 2351-2363 , Springer
• Fredrik N.G. Andersson and Yushu Li (2020)
  • Are Central Bankers Inflation Nutters? An MCMC Estimator of the Long-Memory Parameter in a State Space Model, Computational Economics, 55, pp. 529-549, Springer
• Yushu Li and Jonas Andersson (2019)
  • A Likelihood Ratio and Markov Chain Based Method to Evaluate Density Forecasting (Online, May 17, 2019), ,  Wiley
• Hyunjoo Kim Karlsson, Yushu Li and Ghazi Shukur (2018)
  • The Causal Nexus between Oil Prices, Interest Rates, and Unemployment in Norway Using Wavelet Methods, Sustainability, 10(8), p. 2792
• Bjørn Gunnar Hansen and Yushu Li (2017)
  • An Analysis of Past World Market Prices of Feed and Milk and Predictions for the Future, , 33(2), pp. 175-193, Wiley
• Simon Reese and Yushu Li (2015)
  • Testing for structural breaks in the presence of data perturbations: impacts and wavelet-based improvements, , 85(17), pp. 3468-3479, Taylor & Francis
• Yushu Li (2015)
  • Estimate Long Memory Causality Relationship by Wavelet Method, Computational Economics, 45, pp. 531-544, Springer
• Yushu Li (2014)
  • Estimating and Forecasting APARCH-Skew-t Model by Wavelet Support Vector Machines, Journal of Forecasting, 33(4), pp. 259-269, Wiley
• Yushu Li and Simon Reese (2014)
  • Wavelet improvement in turning point detection using a hidden Markov model: from the aspects of cyclical identification and outlier correction, , 29, pp.1481-1496, Springer
• Yushu Li (2013)
  • Wavelet based outlier correction for power controlled turning point detection in surveillance systems, , 30, pp. 317-321, Elsevier
• Yushu Li and Shukur Ghazi (2013)
  • Testing for Unit Roots in Panel Data Using a Wavelet Ratio Method, Computational Economics, 41, pp. 59-69, Springer
• Yushu Li and Shukur Ghazi (2011)
  • Linear and Nonlinear Causality Test in LSTAR Models: Wavelet Decomposition in Nonlinear Environment, Journal of Statistical Computation and Simulation, 81(12), pp.1913-1925, Taylor & Francis
• Yushu Li and Shukur Ghazi (2011)
  • Wavelet Improvement of the Over-Rejection of Unit Root Test Under GARCH Errors: An Application to Swedish Immigration Data, , 40(13), pp. 2385-2396, Taylor & Francis
• Yushu Li and Shukur Ghazi (2010)
  • Testing for Unit Root Against LSTAR Model: Wavelet Improvement Under GARCH Distortion,  39(2), pp. 277-286, Taylor & Francis

Involved Research Projects

2018-2021 “” (project number 274569). Funded by Finance Market Fund, Norwegian research council, project leader Yushu Li.

2020- 2023 “”. Funded by Research Council of Norway Petromaks-2, project leader Dean Oliver, NORCE.

2021- “”. Funded by Helse Vest, project leader Hans-Peter Marti, Department of Medicine, UIB

2021- 2022 “Predicting Milk Production with Automated Milking System Data”. Funded by Forskningsmidlene for jordbruk og matindustri, project leader Ruohao Sun, Tine SA      

 Educational Project

2022-2023 , funded by UHR-MNT. Reference no. of commitment letter: 21/135-9, project responsible person Yushu Li  

2024 National and International Network building for Actuarial Data Science Educations and Research at Department of Mathematics (MI), Bergen universitetsfond, project responsible person Yushu Li