The first YUIMA Summer School on Computational and Statistical Methods for Stochastic Process & Third Yuima Workshop*
This 4 days course aims at introducing researchers, PhD students and practitioners to several aspects of modern numerical and statistical analysis of time series through the R language and, in particular, the YUIMA package.
The course covers topics of R programming, time series data handling, simulation and numerical analysis for several types of statistical models including: point processes, Hawkes processes,stochastic differential equations driven by Brownian motion with or without jumps, fractional Brownian motion and Lévy processes.
* By invitation only
Third Yuima Workshop program: see this page and schedule of talks here.
Who can benefit?
Stochastic differential equations, with or without jumps, are nowadays used as statistical models in many contexts, including but not limited to, finance, insurance, phylogenetics, genomics, political analysis, economics, migration flow analysis, social network analysis, and more. They are continuous-time models fitted on discrete sampled data. Point processes, like Compound Poisson and Hawkes processes are used in Limit Order Book (LOB) analysis in trading and finance, as well as in the analysis of rainfalls in meteorology or in earthquakes analysis in seismology. Jump and Lèvy processes extends many of the above models to a variety of statistical distributions that are able to capture stylised facts about real time series. Last, but not least, fractional processes are typical tools of climate change studies. Although the course could not cover all of the above applications, the participants can benefit from understanding the simulation and estimation techniques for these classes of stochastic process and apply to their own research field with the help of the faculties of this summer school.
Where & When?
25-28 June 2019, Brixen-Bressanone, Italy
Credits
The Third YUIMA Conference is supported by Japan Science and Technology Agency CREST JPMJCR14D7; and Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research No. 17H01702 (Scientific Research).
Summary
Course Structure
The course consists of:
- Morning lectures: 16 x 45 minutes: Tuesday to Friday 9:00-12:30h
- Practical computer tutorials in the afternoons: Tue, Wed, Fri 14:30-17:00h
Computer Tutorials (Lab)
You will work on the labs at your own pace in small groups with expert guidance (all lecturers from the morning sessions plus teaching assistants).
Participants are required to bring their own laptop with the most recent release versions of R and Yuima installed: we will inform all the participants about detailed installation setup before the course start. Please make sure that your computer’s hardware is sufficiently powered and that you have administrator rights to install further R packages and tools if needed.
Course Materials
The course materials for the labs and lectures will be available for download during and after the course directly from this page in the program table below..
School Programme
Tuesday, June 25
| 9:00-9:45 | Refresh on probability & stochastic processes (Y. Koike) | Lec01 | Slides and R code (updated 2019-06-24) |
| 9:45 – 10:30 | Refresh on statistical inference (S.M. Iacus) | Lec02 | Slides and R code |
| 10:30-11:00 | Coffee break | ||
| 11:00-11:45 | Basics on time series analysis (Y. Koike) | Lec03 | Slides and R code |
| 11:45-12:30 | Monte Carlo analysis (S.M. Iacus) | Lec04 | Slides and R code |
| 12:30-14:30 | Lunch break (lunch self provided by the participants) | ||
| 13:30–14:30 | Installation help desk | ||
| 14:30-15:30 | R programming + time series import and Date/timestamps manipulation in R (E.Guidotti) | Lab01 | Intro to R, Data I/O |
| 15:30-16:00 | Coffee break | ||
| 16:00-17:00 | Overview of Yuima and Yuima GUI (E. Guidotti) | Lab02 | yuima and yuimaGUI |
Wednesday, June 26
| 09:00–09:45 | Refresh on diffusion processes (N. Yoshida) | Lec05 | Slides |
| 09:45–10:30 | Simulation of diffusion processes (H. Masuda) | Lec06 | Slides (updated 2019-06-26) |
| 10:30–11:00 | Coffee break | ||
| 11:00–11:45 | QLA – Quasi-likelihood analysis (N. Yoshida) | Lec07 | Slides |
| 11:45–12:30 | Bayesian analysis (N. Yoshida) | Lec08 | Slides |
| 12:30–14:30 | Lunch break (lunch self provided by the participants) | ||
| 14:30–15:30 | Simulation of diffusion processes (Y. Koike) | Lab03 | Slides and R code (updated 2019-06-25) |
| 15:30–16:00 | Coffee break | ||
| 16:00–17:00 | Estimation for diffusion processes (Y. Koike) | Lab04 | Slides and R code |
Thursday, June 27
| 09:00–09:45 | Lévy processes: basics and simulation (H. Masuda) | Lec09 | Slides, R code and web page |
| 09:45–10:30 | Lévy driven SDE: basics and simulation (H. Masuda) | Lec10 | Slides, R code and web page |
| 10:30–11:00 | Coffee break | ||
| 11:00–11:45 | Quasi-likelihood estimation of Lévy driven SDE (H. Masuda) | Lec11 | Slides, R code and web page |
| 11:45–12:30 | Quasi-likelihood estimation of Lévy driven SDE (H. Masuda) | Lab05 | Slides, R code and web page |
| 12:30–14:30 | Lunch break (lunch self provided by the participants) |
Friday, June 28
| 09:00–09:45 | Point processes: theory and simulation (L. Mercuri) | Lec12 | Slides |
| 09:45–10:30 | Hawkes Processes and LOB (Limit Order Book) models (L. Mercuri) | Lec13 | Slides (updated 2019-06-28) |
| 10:30–11:00 | Coffee break | ||
| 11:00–11:45 | Variance-covariance estimation (Y. Koike) | Lec14 | Slides and R code |
| 11:45–12:30 | Asymptotic expansion methods (N. Yoshida) | Lec15 | Slides and R code |
| 12:30–14:30 | Lunch break (lunch self provided by the participants) | ||
| 14:30–15:30 | Simulation and estimation of compound Poisson and Hawkes processes (L. Mercuri) | Lab06 | Slides and R code |
| 15:30–16:00 | Coffee break | ||
| 16:00–17:00 | Model Selection ans Lasso for SDE models (S.M. Iacus) | Lec16+Lab07 | Slides and R code |
Lecturers and Teaching Assistants
Nakahiro Yoshida (University of Tokyo, JP), Stefano Iacus (University of Milan, IT), Hiroki Masuda (Kyushu University, JP), Lorenzo Mercuri (University of Milan, IT), Yuta Koike (University of Tokyo, JP), Emanuele Guidotti (University of Neuchâtel, CH – AlgoFinance Sagl, CH).
Third YUIMA Workshop Programme (free for students of YSS2019)
Wednesday, June 26
| 17:00-17:05 | Modelling Translation Kinetics after mRNA Transfection Using Diffusions | S. Pieschner (student flash talk) |
| 17:05-17:30 | On regularized estimation for Stochastic Differential Equations | S. M. Iacus |
| 17:30-18:00 | Adaptive L^q penalized estimation for diffusion processes in Yuima package | F. Iafrate |
Thursday, June 27
| 14:30–15:00 | High dimensional covariance estimation in YUIMA package | Y. Koike |
| 15:00–15:30 | Molecular data integration, evolutionary trajectories and diseases | P. Liò |
| 15:30–16:00 | YUIMA for simulating traits and phylogenetics in the pcmabc R package | K. Bartoszek |
| 16:00–16:30 | coffee break | |
| 16:30–17:00 | Point processes modelling of limit order book events | I. Muni Toke |
| 17:00–17:30 | On Lévy driven models in YUIMA | H. Masuda (ask directly the speaker) |
| 17:30–18:00 | Adaptive and non-adaptive estimation of degenerate diffusion processes |
N. Yoshida (ask directly the speaker) |
Friday, June 28
| 17:00–17:05 | Asymptotic equivalence in the Le Cam sense for jump diffusions | G. Gazzani (student flash talk) |
| 17:05–17:30 | COGARCH(p,q) model: simulation, estimation and an application in portfolio selection | L. Mercuri |
| 17:30–18:00 | Towards coding of the asymptotic expansion formula in YUIMA | E. Guidotti |