Will this well enough to serve as a prerequisite to oksendal's stochastic differential equations: an introduction with applications book?
I refer to shiryeav's probability, but i guess it still miss out a lot of detail.
What other books can be a prerequisite too? (Gut's probability:A graduate course is a bit difficult for me (maybe because it is measure theory based?) and measure theory by Cohn book is too difficult for me)
Also, because i want this question to be meaningful, please also list out the prerequisite topics that you know its going to be miss on the oksendal's book.
partial answer here
1)Measure, Integral and Probability by Capinski
2)Probability Essentials by Jacods
3)Knowing the odds by Walsh
are all good but more elemetary than gut