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ePub Continuous Martingales and Brownian Motion (Grundlehren Der Mathematischen Wissenschaften, Vol 293) download

by Daniel Revuz,Marc Yor

ePub Continuous Martingales and Brownian Motion (Grundlehren Der Mathematischen Wissenschaften, Vol 293) download
Author:
Daniel Revuz,Marc Yor
ISBN13:
978-0387576220
ISBN:
0387576223
Language:
Publisher:
Springer-Verlag; 2nd edition (September 1994)
Category:
Subcategory:
Physics
ePub file:
1619 kb
Fb2 file:
1898 kb
Other formats:
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Rating:
4.5
Votes:
260

by Daniel Revuz (Author), Marc Yor (Author). Series: Grundlehren der mathematischen Wissenschaften (Book 293).

by Daniel Revuz (Author), Marc Yor (Author). ISBN-13: 978-3540643258. This is a magnificent book! Its purpose is to describe in considerable detail a variety of techniques used by probabilists in the investigation of problems concerning Brownian motion. The great strength of Revuz and Yor is the enormous variety of calculations carried out both in the main text and also (by implication) in the exercises.

Part of the Grundlehren der mathematischen Wissenschaften book series (GL, volume 293). Bessel process Brownian motion Ergodic theory Markov process Martingale Martingales Stochastic Integration Stochastic Processes local time. Authors and affiliations.

Daniel Revuz, Marc Yor. Springer Science & Business Media, 7 сент Martingales and Brownian Motion Grundlehren der mathematischen Wissenschaften. Springer Science & Business Media, 7 сент. Continuous Martingales and Brownian Motion Grundlehren der mathematischen Wissenschaften (Том 293). Brownian motion Functionals Generator Martingal Martingale brownsche Bewegung diffusion ergodic theory local time probability probability theory stochastic calculus stochastic differential equation stochastic processes stochastische Integration.

Start by marking Continuous Martingales and Brownian Motion as Want to Read . The great strength of Revuz and Yor is the enormous variety o. .

Start by marking Continuous Martingales and Brownian Motion as Want to Read: Want to Read savin. ant to Read. Springer Science & Business Media, 29 июн. 2013 г.This book focuses on the probabilistic theory ofBrownian motion.

This book focuses on the probabilistic theory ofBrownian motion. This is a good topic to center a discussion around because Brownian motion is in the intersec tioll of many fundamental classes of processes. It is a continuous martingale, a Gaussian process, a Markov process or more specifically a process with in dependent increments; it can actually be defined, up to simple transformations, as the real-valued, centered process with independent increments and continuous paths.

Daniel Revuz and Marc Yor, Continuous Martingales and Brownian Motion, 3 e. Grundlehren der matematischen Wissenschaften, vol. 293, Springer, 2005. ENS - DÉPARTEMENT DE MATHÉMATIQUES, TEACHING, 45 rue d'Ulm 75230 Paris Cedex 05, FRANCE - Tel : +33 1 44 32 31 72 -. Contact us. Site map. Legal notices.

The great strength of Revuz and Yor is the enormous variety of calculations carried out both in the main text and also (by implication) in the exercises.

The great strength of Revuz and Yor is the enormous variety of calculations carried out both in the main text and .

  • Very elegant and well written.

  • The book covers exactly what the title says, and it does so in great detail.
    A very good background in measure theory (which I do not have) and a good background in general probability theory are definitely helpful in understanding the topics and the proofs. Mostly, the authors explain well, why they are doing what they are doing now.

    However, particularly in the latter parts of the book, the proofs become more difficult: Instead of filling in the gaps, one reads "it is easy to see that..." or "a moment's reflexion shows..." or...
    I feel, that a little more detailed proofs would much enhance the readability of this book - at the expense of maybe 15 more pages only. This is my reason for four stars only.

    The book has many excercises, which I did not attempt, as no solutions are given. Sometimes the result of an excercise is used in a proof, mimimally for those excercises proofs should have been given.

    I would definitely not recommend this book as a first book on stochastic processes. Particularly the book by Oksendal, and even the book by Karatzas and Shreve are easier to read.

    The book contains very few typos! (I read the version printed in China)

  • This was the text of my second (graduate) course on probability. While going through the text is, with difficulty, manageable with the help of a teacher, I cannot even imagine doing it on my own. The level of difficulty in reading is roughly the same as that of Karatzas and Shreve, though at times the latter is more readable.

    There is a trade-off in learning any new theory. You can get bogged down with the details of every new thing you learn, and move very slowly. While you learn things in detail this way, you miss out on the excitement of learning something new, and perhaps even fail to develop the capability of discerning which concepts are key and which concepts are peripheral to udnerstanding.

    That was my main complaint with Karatzas and Shreve, and it is the same with Revuz and Yor. You can spend DAYS doing the exercises of just Chapter 1. If you think you will remain excited about learning stochastic calculus at a snail's pace for about a year, then this book is for you. What is worse, doing those exercises is absolutely important - some extremely crucial concepts are left as exercises. I shudder to think what the reader who does not have the advantage of having a teacher to discuss with would do when (s)he stumbles upon these exercises. I suspect the only option would be to accept the result and move on.

    I cite an example to prove my point: Exercise 1.4.6 is a crucial concept about stopping times. I believe most people who are reading this book would have done a course that deals with stopping times in discrete time settings. Karatzas and Shreve does contain the proofs of "Exercise 1.4.6" of Revuz and Yor, and the moral there is that the techniques you learnt for discrete time processes do not carry over directly to continuous time. So, if you pass on Exercise 1.4.6 because you could not solve it on your own, you miss out on an extremely useful technique, and therefore your transition from discrete time to continuous time is at least that much incomplete.

    If you are willing to spend a year and a half on stochastic calculus, I would recommend getting a bird's eye view first with something like Oksendal, and then coming down to the details that are omitted there with books like Revuz and Yor and Karatzas and Shreve.

    I think that is a better, more exciting, albeit slower way of learning.