Icef-scalc-2022-fall — различия между версиями
Материал из Wiki - Факультет компьютерных наук
Bdemeshev (обсуждение | вклад) |
Bdemeshev (обсуждение | вклад) |
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| (не показаны 2 промежуточные версии этого же участника) | |||
| Строка 8: | Строка 8: | ||
[https://github.com/bdemeshev/icef_stocalc_2022_fall/tree/main/lecture_notes all handwritten notes] | [https://github.com/bdemeshev/icef_stocalc_2022_fall/tree/main/lecture_notes all handwritten notes] | ||
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| + | [https://github.com/bdemeshev/icef_stocalc_2022_fall/raw/main/ha/ha.pdf Home assignments] | ||
Week 1. Sigma algebras, conditional expected value | Week 1. Sigma algebras, conditional expected value | ||
| Строка 15: | Строка 17: | ||
Week 3. Doob's theorem, ABRACADABRA, Wiener process | Week 3. Doob's theorem, ABRACADABRA, Wiener process | ||
| − | Week 4. Stochastic integral. | + | Week 4. Stochastic integral: intuition |
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| + | Week 5. Stochastic integral: properties, Ito's lemma | ||
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| + | Week 6. Option pricing: binomial, Black and Scholes model. | ||
Текущая версия на 23:54, 8 января 2023
Week 1. Sigma algebras, conditional expected value
Week 2. Conditional variance, geometric viewpoint, martingales, stopping times
Week 3. Doob's theorem, ABRACADABRA, Wiener process
Week 4. Stochastic integral: intuition
Week 5. Stochastic integral: properties, Ito's lemma
Week 6. Option pricing: binomial, Black and Scholes model.
