Open quantitative learning
Econometrics, Time Series & Data Training
Explore a complete ten-chapter English lecture series accompanying Econometrics and Time Series Methods: Theory, Applications, and R Implementation by Yongmiao Hong, Oliver Linton and Jiajing Sun. The learning environment connects econometric intuition, time-series methods, reproducible R implementation, protected lecture slides and self-check questions.
Open access now. All ten lectures and the accompanying online learning resources are currently available free of charge.
Learning environment
One coherent route from theory to reproducible work.
The companion website brings the public lectures, chapter reading, questions, slides and code into one structured learning environment.
10full English video lectures
10chapter slide decks
10guided online chapter notes
10interactive self-check sets
68reproducible R examples
Ten-lecture playlist
Start with the full video series.
Watch the lectures in sequence or move directly to the chapter most relevant to your study or research. The player uses YouTube's privacy-enhanced domain and does not autoplay.
Chapter directory
Ten lectures, with the wider resources one click away.
Each chapter link opens the jointly authored companion environment, where the guide, lecture, self-check questions, slides and public R examples are organised together.
Univariate Time Series
Multivariate Linear Time Series
Volatility Models
Nonparametric Methods
HAR Inference
Filtering & Kalman Methods
Nonstationary Processes
Continuous-Time Finance
Machine Learning in R
Suggested pathway
Watch, review, reproduce, test.
Use the different resources as one learning sequence rather than isolated files.
Build the intuition
Follow the narrated lecture to see how the main ideas and empirical questions fit together.
Return to the slides
Pause over definitions, equations, assumptions and examples that need a second look.
Work through the R code
Run, inspect and adapt the public examples so the methods become operational.
Check your understanding
Use the chapter prompts and self-check questions to identify gaps before moving on.
Continue learning
The wider public resource set.
Companion website βChapter guides, lectures, slides, quizzes and R examples.
QuantLet R archive βPublic, reproducible examples organised around the book.
Quantinar course βA further online route through the course material.
Book information βPublication details and links for the jointly authored text.
From open lectures to tailored training
Discuss a quantitative training requirement.
The open series shows the depth and teaching approach behind this area. JS Insights can also discuss tailored sessions for students, researchers and professional teams, delivered in English, Chinese or bilingually where appropriate.
- Econometrics and time-series methods
- R for financial and economic data
- Forecasting and model evaluation
- Volatility and risk modelling
- Reproducible empirical research workflows
- Tailored workshops for students, researchers and professional teams
Attribution and independence. The companion website and lecture series support Econometrics and Time Series Methods: Theory, Applications, and R Implementation by Yongmiao Hong, Oliver Linton and Jiajing Sun. Book and teaching content remain the property of their respective rights holders. JS Insights is an independent education and training company and is not affiliated with or endorsed by Springer Nature or any university.