Tssp-2024-25

What-about

Course whitepaper

Course goals

侍には目標がなく道しかない [Samurai niwa mokuhyō ga naku michi shikanai]

A samurai has no goal, only a path.

Telegram chat

Grading

Stochastic Processes = 0.35 Halloween Exam + 0.40 Ded Moroz Exam + 0.25 Home Assignments

Time Series Analysis = 0.30 Mimoza Exam + 0.45 Sakura Exam + 0.25 Home Assignments

Home assignments

Home assignments :)

Home assignments have equal weights. You have 4 honey weeks for the whole year.

Exams

Past exams

Midterm alpha: Tuesday, 5 November at 18:10.

Samurai diary: Stochastic Process

Lecture slides and class notes

2024-09-02, lecture 1:

2024-09-09, lecture 2:

2024-09-16, lecture 3: Markov chain: communicating classes. Transient states. Recurrent states.

2024-09-24, lecture 4: Idea of generating function: describe collection of objects as a function and extract information from function. How to extract E(X), E(X^2), E(XY), P(X=3) from a function that generates outcomes. Formal definition of probability generating function and moment generating function.

2024-10-30, lecture 5:

2024-10-07, lecture 6:

2024-10-14, lecture 7: Sigma-algebra is a way to model information, formal definition. Calculating sigma-algebra generated by two events or by discrete random variable. Filtration is a growing sequence of sigma-algebras. Formal definition of conditional expected value with respect to sigma-algebra.

2024-10-21, lecture 8:

2024-12-02, lecture: Girsanov theorem, European option pricing in the Black and Scholes model

Classes

Class video recordings

Maria Kirillova notes

2024-09-06, class 1: First step analysis, 1.1 from StoPro.

More on first step analysis: section 2.7.2 in In2Pro

2024-09-13, class 2: First step analysis, 1.4 from StoPro.

2024-09-20, class 3: Classification of states in Markov chain, communicating classes, 3.1ab from StoPro.

2024-09-27, class 4: Generating functions: standard normal distribution, chi-squared with 1 degree of freedom.

2024-10-04, class 5: Calculating probability limit using LLN. Intuition behind probability limit: unique forecast that is "arbitrary good" for almost all X_n. Probability limit of max and min. Probability limit is a random variable. Probability limit of iid sequence does not exist.

2024-10-11, class 6: Two more limits (in probability and in L2), conditional expected value in uniform case, conditional expected value with joint density.

2024-10-18, class 7: Calculation of sigma-algebra generated by random variable. Calculation of expected value wrt to sigma-algebra.

2024-11-01, class 8: Checking that a process is a martingale, 9.1abcd, 9.9 from StoPro.

2024-11-08, class 9: Poisson point process

2024-11-15, class 10: Doob's optional stopping time theorem in discrete time

2024-11-22, class 11: Calculating E, Cov, Var for Wiener process, (W_t) and (W_t^2 - t) are martingales

2024-11-29, class 12: Ito's integral for a piece-wise constant process, Ito's lemma, martingale condition

2024-12-06, class 13: more Ito's lemma and stochastic integral properties.

2024-12-13, class 14: binomial tree, finding risk neutral probabilities, European and American call option.

Samurai diary: Time series

2025-01-09, lecture 1: Weakly and strictly stationary processes: definition, examples, MA(q) process, autocovariance and autocorrelation function

2025-01-16, lecture 2: Non-uniqueness of MA(q) equation, invertibility of MA(q) process: definition and criterion, characteristic MA-polynomial, MA(infty) process, AR(p)-equation, example of infinitely many solutions of AR(1)-equation.

2025-01-17, class 1: Stationarity, MA-process

Sources of Wisdom

StoPro: Problems in Stochastic Processes

In2Pro: Blitstein, Hwang, Introduction to probability.

MarkovTex: Representing Markov Chains in Latex.

Mchains Cambridge lectures on Markov chains.

Takis: Takis Konstantinopulos, One hundred solved exercises on Markov chains.

Past course iterations: 2023-2024, 2022-2023, 2021-2022, 2020-2021.

Convergence modes review from Cornell university

Convergence modes: Saravan Vijayakumaran, convergence modes with examples