Time Series and Stochastic Processes ada 21 22 — различия между версиями
Bdemeshev (обсуждение | вклад) (→Week progress) |
Bdemeshev (обсуждение | вклад) (→Semester II) |
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| Строка 150: | Строка 150: | ||
3.2. Equations is not a process. | 3.2. Equations is not a process. | ||
| − | Two problems from Econometrics Olympiad: [https://github.com/bdemeshev/tssp_2021-22/raw/main/notes/tssp_2021-22_2022-01-27-sem2_class_03_2_a_rus.pdf pdf-a], [https://github.com/bdemeshev/tssp_2021-22/raw/main/notes/tssp_2021-22_2022-01-27-sem2_class_03_2_b_eng.pdf pdf-b], [https://github.com/bdemeshev/tssp_2021-22/raw/main/notes/tssp_2021-22_2022-01-28-sem2_class_03_2_c_rus.pdf pdf-c]. | + | Two problems from [https://new.universiade-ecm.com/ Econometrics Olympiad]: [https://github.com/bdemeshev/tssp_2021-22/raw/main/notes/tssp_2021-22_2022-01-27-sem2_class_03_2_a_rus.pdf pdf-a], [https://github.com/bdemeshev/tssp_2021-22/raw/main/notes/tssp_2021-22_2022-01-27-sem2_class_03_2_b_eng.pdf pdf-b], [https://github.com/bdemeshev/tssp_2021-22/raw/main/notes/tssp_2021-22_2022-01-28-sem2_class_03_2_c_rus.pdf pdf-c]. |
==== Week 4 ==== | ==== Week 4 ==== | ||
Версия 22:42, 3 февраля 2022
General course info
- Boring official web page
- teams group: all class videos are there :)
Teachers and assistants
Lecturer: Peter Lukianchenko
Class teacher: Boris Demeshev
Semester I
Week 01
Lecture: [1]
Class: First step analysis, expected time to get HTH.
Week 02
Lecture: [2]
Class: Markov chain states classification
Week 03
Lecture: [3]
Class: Poisson process.
Week 04
Lecture: [4]
Class: Conditional expected value. Conditional variance.
Week 05
Lecture: [5]
Class: Sigma-algebras, measurability. Conditional expected value with respect to sigma-algebra.
Week 06
Lecture:
Class: Probability limit, Moment generating function
Midterm
The long-awaited midterm will be on 28 October, 10:00 - 12:00.
Duration: 120 minutes. No proctoring.
Topics:
- First step analysis
- Classification of states and classes of MC.
- Conditional expected value (two views).
- Poisson process.
- Sigma algebras.
- Probability limit
- Moment generating function
Week
Date: 2021-10-28
Lecture:
Class: Martingales in discrete time
Week
Date: 2021-11-09
Lecture:
Class: Wiener process definition, basic properties, inversion
Week
Date: 2021-11-16
Lecture:
Class: Stochastic integral, intuition, limit in L2
Week
Date: 2021-11-23
Lecture:
Class: Stochastic integral properties, Ito's lemma
Week
Date: 2021-11-30
Lecture:
Class: BS model, Girsanov theorem, pricing
Week
Date: 2021-12-07
Lecture:
Class: more pricing examples in BS model
Week
Date: 2021-12-14
Lecture:
Class: Recap on martingales, Ito, etc
Semester II
Week 1
1.1.
1.2.
Week 2
2.1.
2.2.
Week 3
3.1.
3.2. Equations is not a process. Two problems from Econometrics Olympiad: pdf-a, pdf-b, pdf-c.
Week 4
4.1. Solutions of recurrence equation: pdf-a, pdf-b, pdf-c.
4.2. Roots of lag and characteristic equation: pdf-a, pdf-b, [pdf-c].
Sources
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
