Tssp-2022-23 — различия между версиями
Maximfish (обсуждение | вклад) м |
(→Sources) |
||
(не показано 46 промежуточных версии 4 участников) | |||
Строка 1: | Строка 1: | ||
== General course info == | == General course info == | ||
− | * Boring [https://www.hse.ru/edu/courses/ | + | * Boring [https://www.hse.ru/edu/courses/749646288 official] web page |
+ | ==== Grading ==== | ||
+ | Fall grade = 0.3 HAs + 0.7 October Exam | ||
− | = Teachers and assistants = | + | Final grade = 0.2 Fall grade + 0.25 HAs + 0.15 December Midterm + 0.25 Spring Midterm + 0.15 Final Exam |
+ | |||
+ | Actual grades: [https://docs.google.com/spreadsheets/d/e/2PACX-1vQqRvmRVq-b2olpbl_028gjSsoVdR2cANoTyDXhaYjTCQELwjECBgj2oljHsXC8XlkGrXx2up-ebrAh/pub?output=xlsx xlsx], [https://docs.google.com/spreadsheets/d/e/2PACX-1vQqRvmRVq-b2olpbl_028gjSsoVdR2cANoTyDXhaYjTCQELwjECBgj2oljHsXC8XlkGrXx2up-ebrAh/pubhtml html] | ||
+ | |||
+ | ==== Teachers and assistants ==== | ||
Lecturer: [https://www.hse.ru/org/persons/14276760 Peter Lukianchenko] | Lecturer: [https://www.hse.ru/org/persons/14276760 Peter Lukianchenko] | ||
− | Class teacher: [https://www.hse.ru/staff/bbd Boris Demeshev], Sveta Popova, Maria Kirillova | + | Class teacher: [https://www.hse.ru/staff/bbd Boris Demeshev], [https://www.hse.ru/org/persons/14288706 Sveta Popova], Maria Kirillova |
+ | ==== [https://github.com/bdemeshev/tssp_2022-23/raw/main/ha/tssp_ha.pdf Home assignments] ==== | ||
+ | ==Log Book == | ||
+ | ==== Semester I ==== | ||
− | == | + | Нажми "развернуть", чтобы просмотреть содержимое - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 🡣 |
+ | <div class="mw-collapsible mw-collapsed" style="width:1000px; overflow: hidden;"> | ||
+ | |||
+ | '''Week 1. 2022-09-03''' | ||
+ | |||
+ | Lecture. Markov chains, transition matrix, [https://github.com/bdemeshev/tssp_2022-23/raw/main/lectures/TSSP_m1_l1_DSBA3_2022.pdf pdf] | ||
+ | |||
+ | Class. Transition matrix, first step analysis. | ||
+ | |||
+ | More: | ||
+ | |||
+ | [http://www.statslab.cam.ac.uk/~rrw1/markov/ Cambridge course] on Markov chains | ||
+ | |||
+ | '''Week 2. 2022-09-10''' | ||
+ | |||
+ | Lecture. Markov chains, stationary distribution, modes of convergence, [https://github.com/bdemeshev/tssp_2022-23/raw/main/lectures/TSSP_m1_l2_DSBA3_2022.pdf pdf] | ||
+ | |||
+ | Class. Stationary distribution, modes of convergence | ||
+ | |||
+ | '''Week 3. 2022-09-17''' | ||
+ | |||
+ | Lecture. Markov process, math modelling, [https://github.com/bdemeshev/tssp_2022-23/raw/main/lectures/TSSP_m1_l3_DSBA3_2022.pdf pdf] | ||
+ | |||
+ | Class. plim, almost sure lim | ||
+ | |||
+ | '''Week 4. 2022-09-24''' | ||
+ | |||
+ | Lecture. Conditional expectation, [https://github.com/bdemeshev/tssp_2022-23/raw/main/lectures/TSSP_m1_l4_DSBA3_2022.pdf pdf] | ||
+ | |||
+ | Class. Conditional expectation, sigma algebra, [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/tssp-2022-09-26-class_4a-sigma-algebra.pdf 4a], [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/tssp-2022-09-29-class_4b-sigma-algebra.pdf 4b] | ||
+ | |||
+ | '''Week 5. 2022-10-01''' | ||
+ | |||
+ | Lecture. First-step analysis, sigma algebra [https://github.com/bdemeshev/tssp_2022-23/raw/main/lectures/TSSP_m1_l5_DSBA3_2022.pdf pdf] | ||
+ | |||
+ | Class. Conditional expectation and variance, sigma algebra, [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/tssp-2022-10-03-class_5a-conditional-e-var.pdf 5a], [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/tssp-2022-10-06-class_5b-conditional-e-var.pdf 5b] | ||
+ | |||
+ | '''Week 6. 2022-10-08''' | ||
+ | |||
+ | Lecture. Basics of stochastic processes [https://github.com/bdemeshev/tssp_2022-23/raw/main/lectures/TSSP_m1_l6_DSBA3_2022.pdf pdf] | ||
+ | |||
+ | Class: Martingales, filtration, [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/tssp-2022-10-10-class_6a-martingales.pdf 6a], [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/tssp-2022-10-13-class_6b-martingales.pdf 6b] | ||
+ | |||
+ | '''Week 7. 2022-10-15''' | ||
+ | |||
+ | Lecture. Brownian motion (Wiener process), filtration in continuous time [https://github.com/bdemeshev/tssp_2022-23/raw/main/lectures/TSSP_m1_l7_DSBA3_2022.pdf pdf] | ||
+ | |||
+ | Class: Poisson process, [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/tssp-2022-10-20-class_7a-poisson-process.pdf 7a], [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/tssp-2022-10-20-class_7b-poisson-process.pdf 7b] | ||
+ | |||
+ | '''Week 8. 2022-10-22''' | ||
+ | |||
+ | Lecture. Wiener process (additional exercises) [https://zoom.us/rec/share/19THFlfbJsToxi_xiEt3sdXcCtkgbcfBneKULjwjLDUGfBnJDgHSR4Z3EHDKCWA_.t93R85fWqce0aImX video], [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/tssp-2022-10-22-class_8-wiener-process.pdf pdf] | ||
+ | |||
+ | Class: Solve midterm tasks | ||
+ | |||
+ | '''Week 9. 2022-11-05''' | ||
+ | |||
+ | Lecture. Stochastic integral, Ito formula [https://github.com/bdemeshev/tssp_2022-23/raw/main/lectures/TSSP_m2_l1_DSBA3_2022.pdf pdf] | ||
+ | |||
+ | Class: Stochastic integral, L2 convergence | ||
+ | |||
+ | '''Week 10. 2022-11-12''' | ||
+ | |||
+ | Lecture. Ito's lemma, BS model [https://github.com/bdemeshev/tssp_2022-23/raw/main/lectures/TSSP_m2_l2_DSBA3_2022.pdf pdf] | ||
+ | |||
+ | Class: Stochastic integral (Wu dWu), L2 convergence | ||
+ | |||
+ | '''Week 11. 2022-11-19''' | ||
+ | |||
+ | Lecture. BS solution [https://github.com/bdemeshev/tssp_2022-23/raw/main/lectures/TSSP_m2_l3_DSBA3_2022.pdf pdf] | ||
+ | |||
+ | Class: Ito's lemma | ||
+ | |||
+ | '''Week 12. 2022-11-26''' | ||
+ | |||
+ | Lecture. Binomial tree, risk-neutral probability [https://github.com/bdemeshev/tssp_2022-23/raw/main/lectures/TSSP_m2_l4_DSBA3_2022.pdf pdf] | ||
+ | |||
+ | Class: BS model, SDE | ||
+ | |||
+ | </div> | ||
+ | |||
+ | |||
+ | ==== Semester II ==== | ||
+ | |||
+ | '''Week 1. 2023-01-14''' | ||
+ | |||
+ | Lecture. Intro to Time Series, stationarity, ACF, PACF [https://github.com/bdemeshev/tssp_2022-23/raw/main/lectures/TSSP_m3_l1_DSBA3_2022.pdf pdf] | ||
+ | |||
+ | Class: White noise, stationarity [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/w01a-white-noise-stationarity.pdf online-A], [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/w01b-white-noise-stationarity.pdf online-B] | ||
+ | |||
+ | '''Week 2. 2023-01-21''' | ||
+ | |||
+ | Lecture. ARMA process, more ACF/PACF [https://github.com/bdemeshev/tssp_2022-23/raw/main/lectures/TSSP_m3_l2%263_DSBA3_2022.pdf pdf] | ||
+ | |||
+ | Class: ACF, PACF [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/w02a-acf-pacf.pdf online-A], [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/w02a-acf-pacf.pdf online-B] | ||
+ | |||
+ | '''Week 3. 2023-01-28 ''' | ||
+ | |||
+ | Lecture. ARMA process, more ACF/PACF [https://github.com/bdemeshev/tssp_2022-23/raw/main/lectures/TSSP_m3_l2%263_DSBA3_2022.pdf pdf] | ||
+ | |||
+ | Class: recurrence equations and AR(1), Yule-Wolker equations for PACF [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/w03a-ar1-more-pacf.pdf online-A], [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/w03a-ar1-more-pacf.pdf online-B] | ||
+ | |||
+ | '''Week 4. 2023-02-04 ''' | ||
+ | |||
+ | Lecture. Forecasting with ARMA, ADF [https://github.com/bdemeshev/tssp_2022-23/raw/main/lectures/TSSP_m3_l4_DSBA3_2022.pdf pdf] | ||
+ | |||
+ | Class. Forecasting with AR, MA(infty) solutions [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/w04a-ma-infinity-solution.pdf online-A], [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/w04b-ma-infinity-solution.pdf online-B] | ||
+ | |||
+ | '''Week 5. 2023-02-11 ''' | ||
+ | |||
+ | Lecture. Non-Stationary Time Series, Holt-Winter's exponential smoothing [https://github.com/bdemeshev/tssp_2022-23/raw/main/lectures/TSSP_m3_l5_done.pdf pdf] | ||
+ | |||
+ | Class. ACF, PACF for ARMA(1,1), AR(2) [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/w05a-arma11-pacf-interpretation online-A], [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/w05b-arma11-pacf-interpretation.pdf online-B] | ||
+ | |||
+ | '''Week 6. 2023-02-18 ''' | ||
+ | |||
+ | Lecture. ETS-model [https://github.com/bdemeshev/tssp_2022-23/raw/main/lectures/TSSP_m3_lecture-2023-02-18_ets-problems.pdf pdf] | ||
+ | |||
+ | Class. ETS(AAA) [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/w06a-ets-aaa.pdf, online-A], [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/w06b-ets-aaa.pdf online-B] | ||
+ | |||
+ | '''Week 7. 2023-02-25 ''' | ||
+ | |||
+ | Lecture. GARCH [https://github.com/bdemeshev/tssp_2022-23/raw/main/lectures/TSSP_m3_l7.pdf pdf] | ||
+ | |||
+ | '''Week 8. 2023-03-04''' | ||
+ | |||
+ | Lecture. UOL - point, interval estimators [https://github.com/bdemeshev/tssp_2022-23/raw/main/lectures/TSSP_m3_l8.pdf pdf] | ||
+ | |||
+ | '''Week 9. 2023-03-11 ''' | ||
+ | |||
+ | Lecture. UOL - Fisher info [https://github.com/bdemeshev/tssp_2022-23/raw/main/lectures/TSSP_m3_l9.pdf pdf] | ||
+ | |||
+ | Class. Fisher info | ||
+ | |||
+ | '''Week 10. 2023-03-18 ''' | ||
+ | |||
+ | Lecture. UOL | ||
+ | |||
+ | '''Week 11. 2023-03-25 ''' | ||
+ | |||
+ | Midterm | ||
+ | |||
+ | == Sources == | ||
+ | * [https://github.com/bdemeshev/tssp_exams/raw/main/tssp_exams.pdf all past exams] | ||
+ | * [https://github.com/bdemeshev/tssp_2022-23/tree/main/online_classes handwritten class notes] | ||
* [http://wiki.cs.hse.ru/Time_Series_and_Stochastic_Processes_ada_20_21 Wiki 2020-21], [http://wiki.cs.hse.ru/Time_Series_and_Stochastic_Processes_ada_21_22 Wiki 2021-22] | * [http://wiki.cs.hse.ru/Time_Series_and_Stochastic_Processes_ada_20_21 Wiki 2020-21], [http://wiki.cs.hse.ru/Time_Series_and_Stochastic_Processes_ada_21_22 Wiki 2021-22] | ||
* [https://github.com/bdemeshev/tssp/tree/master/2020_2021 Git repo 2020-21], [https://github.com/bdemeshev/tssp_2021-22/ Git repo 2021-22] | * [https://github.com/bdemeshev/tssp/tree/master/2020_2021 Git repo 2020-21], [https://github.com/bdemeshev/tssp_2021-22/ Git repo 2021-22] | ||
* [https://t.me/TSSP22 TG chat 2022-23] | * [https://t.me/TSSP22 TG chat 2022-23] | ||
+ | * [https://www.youtube.com/playlist?list=PLGpdGKp2JUvygvPGgYZLNoC82Ug8Fd81L видео очных семинаров 2022-23], [https://disk.yandex.ru/d/ceN8JNGEE1GE5Q видео Zoom семинаров 2022-23] | ||
+ | * [https://disk.yandex.com.ge/d/o_QCTfVi_hLQSA видео консультаций 2022-23 на русском] | ||
* [https://github.com/mavam/stat-cookbook/releases/download/0.2.6/stat-cookbook.pdf Statistics cookbook] | * [https://github.com/mavam/stat-cookbook/releases/download/0.2.6/stat-cookbook.pdf Statistics cookbook] | ||
Строка 73: | Строка 228: | ||
* [https://robjhyndman.com/uwafiles/9-StateSpaceModels.pdf Rob Hyndman, State Space Models] | * [https://robjhyndman.com/uwafiles/9-StateSpaceModels.pdf Rob Hyndman, State Space Models] | ||
− | |||
− |
Текущая версия на 11:31, 24 марта 2023
Содержание
General course info
- Boring official web page
Grading
Fall grade = 0.3 HAs + 0.7 October Exam
Final grade = 0.2 Fall grade + 0.25 HAs + 0.15 December Midterm + 0.25 Spring Midterm + 0.15 Final Exam
Teachers and assistants
Lecturer: Peter Lukianchenko
Class teacher: Boris Demeshev, Sveta Popova, Maria Kirillova
Home assignments
Log Book
Semester I
Нажми "развернуть", чтобы просмотреть содержимое - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 🡣
Semester II
Week 1. 2023-01-14
Lecture. Intro to Time Series, stationarity, ACF, PACF pdf
Class: White noise, stationarity online-A, online-B
Week 2. 2023-01-21
Lecture. ARMA process, more ACF/PACF pdf
Class: ACF, PACF online-A, online-B
Week 3. 2023-01-28
Lecture. ARMA process, more ACF/PACF pdf
Class: recurrence equations and AR(1), Yule-Wolker equations for PACF online-A, online-B
Week 4. 2023-02-04
Lecture. Forecasting with ARMA, ADF pdf
Class. Forecasting with AR, MA(infty) solutions online-A, online-B
Week 5. 2023-02-11
Lecture. Non-Stationary Time Series, Holt-Winter's exponential smoothing pdf
Class. ACF, PACF for ARMA(1,1), AR(2) online-A, online-B
Week 6. 2023-02-18
Lecture. ETS-model pdf
Class. ETS(AAA) online-A, online-B
Week 7. 2023-02-25
Lecture. GARCH pdf
Week 8. 2023-03-04
Lecture. UOL - point, interval estimators pdf
Week 9. 2023-03-11
Lecture. UOL - Fisher info pdf
Class. Fisher info
Week 10. 2023-03-18
Lecture. UOL
Week 11. 2023-03-25
Midterm
Sources
- all past exams
- handwritten class notes
- Wiki 2020-21, Wiki 2021-22
- Git repo 2020-21, Git repo 2021-22
- TG chat 2022-23
- видео очных семинаров 2022-23, видео Zoom семинаров 2022-23
- видео консультаций 2022-23 на русском
MC + MCMC
- James Norris, Markov chains (1998, no kernels)
- Cambridge course on Markov chains
- Chib and Greenberg, Understanding MH algorithm
- Casella, Explaining Gibbs Sampler
- Roberts and Rosenthal, General State Space Markov Chains
- Charles Geyer, MCMC lecture notes (with a little bit of kernels!)
Stochastic Calculus
- Zastawniak, Basic Stochastic Processes
Time Series
- Van der Vaart, Time Series
UCM
- Harvey Jaeger, Detrending, Stylized Facts and the Business Cycle
- João Tovar Jalles, Structural Time Series Models and the Kalman Filter