Time Series and Stochastic Processes ada 20 21

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General course info

Week progress

Week 01

  • Sigma-algebras, measurability of random variable with respect to sigma-algebra.
  • Seminar 01

Week 02

  • Markov chain. Classification of states. Calculations of return probability, mean return time, stationary distribution.
  • Seminar 02a, 02b
  • Cambridge Markov chain course. There you may find useful: lecture notes, past tripos and more.

Week 03

  • Conditional expected value. Martingales.

Week 04

Week 05

  • Wiener process: basic properties, inversion

Week 06

  • Wiener process: limit in L2

Week 07

Ito integral WtdWt, Ito's lemma


Stochastic Calculus

  • Zastawniak, Basic Stochastic Processes

Time Series



  • James Norris, Markov chains (1998, no kernels)