Chevron Left
Zurück zu Stochastische Prozesse

Kursteilnehmer-Bewertung und -Feedback für Stochastische Prozesse von National Research University Higher School of Economics

4.5
Sterne
291 Bewertungen
74 Bewertungen

Über den Kurs

The purpose of this course is to equip students with theoretical knowledge and practical skills, which are necessary for the analysis of stochastic dynamical systems in economics, engineering and other fields. More precisely, the objectives are 1. study of the basic concepts of the theory of stochastic processes; 2. introduction of the most important types of stochastic processes; 3. study of various properties and characteristics of processes; 4. study of the methods for describing and analyzing complex stochastic models. Practical skills, acquired during the study process: 1. understanding the most important types of stochastic processes (Poisson, Markov, Gaussian, Wiener processes and others) and ability of finding the most appropriate process for modelling in particular situations arising in economics, engineering and other fields; 2. understanding the notions of ergodicity, stationarity, stochastic integration; application of these terms in context of financial mathematics; It is assumed that the students are familiar with the basics of probability theory. Knowledge of the basics of mathematical statistics is not required, but it simplifies the understanding of this course. The course provides a necessary theoretical basis for studying other courses in stochastics, such as financial mathematics, quantitative finance, stochastic modeling and the theory of jump - type processes. Do you have technical problems? Write to us: coursera@hse.ru...

Top-Bewertungen

CR

Sep 14, 2019

This was helpful but I still feel I don't understand stochastic processes. Folks taking this course should know that it's pretty tough, compared to most Coursera courses.

MM

Sep 23, 2019

Great course! The subject material was well covered and it gave me the tools to tackle more advanced stochastic, like population dynamics or quantitative finance.

Filtern nach:

51 - 74 von 74 Bewertungen für Stochastische Prozesse

von Desetti S P

Jun 03, 2020

good

von maraka d r

Apr 10, 2019

nice

von Jonathan

Jan 15, 2020

This was a good class, but it is probably a bit unique among a lot of the options you have in Coursera.

General Overview:

This class is ENTIRELY about the formal mathematical principles surrounding a very specific, niche academic topic. You won't need to touch a computer to do any of the assignments, and the course material is entirely comprised of mathematically formulating a bunch of different concepts.

Best Parts:

In terms of subject material, this is without a doubt one of the most unique classes on Coursera. It covers a variety of unique concepts that I don't think are covered anywhere else, and by the time you're finished you're covering material that is very differentiated. There's really not a lot of coverage anywhere about something like a Levy Process........this is the exact kind of thing you'd probably have to go to graduate school in order to get exposure to, and for a lot of the material covered, many of the top google links about my queries were the lecture videos I was watching about the topic at hand.

This class is very useful for refining your mathematical pedigree. If you feel like you're weak on on formal math and are trying to bootstrap your own knowledge on quantitative topics, there are probably few better resources than a class like this.

Worst Parts:

There is basically no attempt to go into useful, practical applications of the material covered. None of the examples given in class are concrete, and basically everything is covered at the level of derivatives and integrals on a whiteboard. After 8 weeks I still wouldn't have much of an idea about how to actually implement most of the things covered in class.

I DO have some useful memory pointers about the formal theory behind a lot of interesting things that I didn't have before, but if I actually wanted to model insurance claims according to a compound poisson process I don't think I'd know where to start.

There is no attempt to simplify the material, and a good amount of background knowledge is assumed in the coverage of class material. So be prepared to do some additional work on your own if you want to be able to fully understand the contents of the material.

Overall, I found this to be a unique class with certain benefits I don't think I would find anywhere else on the internet. And while it is very particular in what it does and doesn't do for you, I found it to be a worthwhile endeavor and enjoyed the chance to engage with its material.

von Moreno C

Oct 23, 2019

This is an intense mathematics course which requires a strong previous knowledge of single variable calculus and probability theory.

I have learned a lot and I was happy with the classic theorem/proof teaching style of the instructor.

Nonetheless, I would have found beneficial adding to the rigorous proofs some recitations dedicated to potential applications of the theoretical tools developed during the course.

von 周昊晟

Aug 09, 2019

This course is a very good course to have an extensive view on stochastic process. Although rigorous proofs are not given for some of the theorems, the class is still worth learning.

von Leandro S P

Dec 29, 2018

The content of the course is excellent and the lectures are very clear. However, there are recurrent errors in the exercises and even in the final exam which have not been corrected.

von Luis M

Feb 17, 2020

The course was really good but some pdf with detailed problems or some videos with tangible examples could have made it perfect.

von Aditi M

Mar 11, 2020

Course was outlined very well. Basic definitions with examples and important theorems were covered efficiently.

von 韩

Nov 27, 2018

Please give us the explanation of the exercises, because I don't understand why my answer is wrong.

von Luan S d B

Aug 02, 2019

O curso deveria ter mais exemplos que se encaixam na vida real. A parte teórica foi excelente.

von DropRooster

Mar 05, 2020

Very good introduction course, but with few mistakes in the lectures, quizs and final.

von Dmitry

Nov 13, 2018

Nice course but a lot of typos in the slides.

von akash s

Jun 04, 2020

hard course

von CHIA-WEI L

Jul 23, 2020

excellent!

von Johnnie R P

Jun 23, 2020

Great!!

von Zixu Z

May 03, 2020

The course is of mixed experiences. I enjoyed the clear derivations and proofs. However, after introducing a lot of seemly important concepts and spending a lot of time in proofs, there are barely any content on why we are doing these. OK, I got it that things like ergodicity, spectral functions seems important since the instructor spent more than half an hour showing the proofs and properties, but then the instructor stopped without mentioning anything about if a stochastic process is ergodic, then what? To me, I learned many new fancy terms but still have little ideas of how it can be helpful if I try to look at a stock price process, for example.

von Samyak J

May 29, 2020

Good course, but the theory is sometimes ill-explained or skipped. Also, it would be a lot better if there were more examples and practical questions.

von Chen N

Jan 05, 2019

Nice course :) But it takes time to be adopted to the teaching style...

von yash

Jun 03, 2019

mediocre explanation and lack of exercise.

von Meilu L

Oct 25, 2018

It is difficult to understand

von Long Y

Jun 15, 2018

Too many errors in the quiz. It makes students confused about what is asked and why the answer is that. Students keep guessing what the question is asking or what typo the correct answer may have.

von Huanfeng Y

Mar 07, 2020

The course is too abstruse and cramming. DO NOT recommend it for anyone who are looking for a solid and indepth understanding of stochastic processes.

von Omar S

Apr 14, 2020

It is very dry math. Sometimes, the symbols just come out of no where. I was hoping for something for oriented towards applications, and some computational approach to the topic.

von Manav A

Jul 11, 2020

course doesn't provide adequate intuition of the subject matter which is very crucial for it,