Surprised nobody mentioned Stein & Shakarchi
I need a 'Measure Theory for Complete rtards' book

If you don't have math background then don't pursue quant finance topics. You're just asking for pain.
This. It takes enormous amount of effort to learn math properly. The book by Axler mentioned above states you should devote at least 1 hour for 1 page (and that might be too fast). And then you should attempt exercises (as many as possible) and try to solve them yourself. Few people have that amount of devotion and time later in life.

You guys are clueless about this stuff. The abrasct measure spaces come up frequently in many finance areas. Lebesgue integration is not useful.
Integration is an integral part of probability, obviously. The space of Riemann integrable functions is not complete, which is a severe limitation for establishing many crucial theoretical results that are of practical use. So yes, Lebesgue integration is useful.

The reason you end up with a sigma algebra is because the collection that satisfies the Caratheodory criterion happens to be one. And then yoour outer measure is actually countably additive over this (and it also extends the proto measure over the semi ring from which the outer measure was generated)

The reason you end up with a sigma algebra is because the collection that satisfies the Caratheodory criterion happens to be one. And then yoour outer measure is actually countably additive over this (and it also extends the proto measure over the semi ring from which the outer measure was generated)
Sir, this thread is about tards, what is Carad theory

The reason you end up with a sigma algebra is because the collection that satisfies the Caratheodory criterion happens to be one. And then yoour outer measure is actually countably additive over this (and it also extends the proto measure over the semi ring from which the outer measure was generated)
I guess now I know why it wasn't covered

You dont need measure theory to understand SDEs etc.
Evans has a book that develops everything needed in ECON without measure theory.Evans is good enough only to have some understanding of what you read. But definitely not good enough if you want to do rigorous research using stochastic calculus.
Saying that, it is also true that many economists who use continuous time have little understanding of technicalities, and that's why there are plenty of papers that include incorrect results, or claims that might be correct but the proofs are incomplete.Are those technicalities really crucial ?
I doubt.
Measure theory is much like rest of real analysis: the critical parts only show in pathological instances, and rest is common sense.Yes, in continuous time those technicalities are crucial.
Give me an example where some not obvious measure theory is needed, or else one ends up with wrong result.
obvious measure theory is when you think of it as a weight function and do what you want to do.

It,s rarely used in probability. Just use calculus to compute. The abstract concepts and tools of measure theory are much more useful. Things like information flow, conditional expectation, etc.
You guys are clueless about this stuff. The abrasct measure spaces come up frequently in many finance areas. Lebesgue integration is not useful.
Integration is an integral part of probability, obviously. The space of Riemann integrable functions is not complete, which is a severe limitation for establishing many crucial theoretical results that are of practical use. So yes, Lebesgue integration is useful.

Yes, in continuous time those technicalities are crucial.
Give me an example where some not obvious measure theory is needed, or else one ends up with wrong result.
obvious measure theory is when you think of it as a weight function and do what you want to do.Try proving that Brownian motion exists without measure theoretic results like the Kolmogorov extension and continuity theorems.

Honestly, ask your instructor. People like your instructor learn measure theory some time in their lives and the particular book / approach shapes what they are telling. Asking for advice from them makes your life easier. Measure theory is a necessary chore to get used to, there is no inherent value / beauty / insightsto it at your level. Not even at the level of a theoretical econometrician. It's just a framework for speaking about probabilities.
Most of it is on wikipedia anyways.

Axler's new book is perhaps the clearest and easiest to learn from measure theory book written to day, in my opinion. And, the electronic version is free. So take a look:
https://measure.axler.net/It's been a month and I can't understand anything. What's the real difference between fields and sigmafields? Why do we even want do define everything on them? What's the relationship between Borel sets and real numbers? What the hell did Radon and his pal really prove?
I just don't get anything. For Christ's sake, I was a business studies major.
Wow, I just started reading this after seeing it here and got through the first two chapters without even noticing. This is a fantastically written book!

Axler's new book is perhaps the clearest and easiest to learn from measure theory book written to day, in my opinion. And, the electronic version is free. So take a look:
https://measure.axler.net/It's been a month and I can't understand anything. What's the real difference between fields and sigmafields? Why do we even want do define everything on them? What's the relationship between Borel sets and real numbers? What the hell did Radon and his pal really prove?
I just don't get anything. For Christ's sake, I was a business studies major.
Wow, I just started reading this after seeing it here and got through the first two chapters without even noticing. This is a fantastically written book!
Yes, it is a real gem.

I don't know why people don't recommemd this brilliant book: https://www.cambridge.org/core/books/realanalysisandprobability/26DDF2D09E526185F2347AA5658B96F6
The first 5 chapters effectively replaces Baby Rudin and Royden. The remaining ones are all about probability.

I don't know why people don't recommemd this brilliant book: https://www.cambridge.org/core/books/realanalysisandprobability/26DDF2D09E526185F2347AA5658B96F6
The first 5 chapters effectively replaces Baby Rudin and Royden. The remaining ones are all about probability.Oh for phuk's sake. For the dozenth time, it is specifically because OP asked for "a 'Measure Theory for Complete rtards' ".
Dudley's book is aimed at graduate students in mathematics. When it first appeared in 1990, it was heralded as establishing a new standard of rigor and completeness for the decade.
Does that sound like what OP is asking for? Hmmmmm?
From the "Most Helpful" review on Amazon:
"I have been teaching a one semester course of Real Analysis (measure and integration) from this book. The students have already been through a course based on Rudin's Principles of Mathematical Analysis though not the Lebesgue integral there, and pretty comfortable with metric spaces and such and the standards of mathematical proof. So as the next step in analysis this book seems to be in the right place esp. because the book advertises itself as selfcontained.
While I appreciate the wonderful integration of Real Analysis and Probability and short proofs, the brevity is often achieved by omitting details rather than choosing a simpler argument and so the book is a bit too hard on the students. Many proofs are too terse and have significant gaps which often take a lot of classroom time to get over, unless you are willing to leave them puzzled. The wording in the proofs is often counterintuitive, in particular it is usually not clear if the sentence continues the line of argument or starts a new one. This is an unnecessary hiccup for the reader and it would cost just few friendly words here and there to fix. Overall the book is harder to follow than Royden's Real Analysis. Many of the exercises are great and illuminative but many are just impossibly hard."

Lol
I don't know why people don't recommemd this brilliant book: https://www.cambridge.org/core/books/realanalysisandprobability/26DDF2D09E526185F2347AA5658B96F6
The first 5 chapters effectively replaces Baby Rudin and Royden. The remaining ones are all about probability.