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Sorry to bother you, and I'm not entirely sure this is the correct place to be discussing this but I shall try to be brief.

I'm a complete rookie when it comes to anything stochastic/probability based - I only have an undergraduate course in measure theory under my belt with beginner level courses in Python. However, I'd like to write a thesis on applying techniques from probability theory (Brownian motion/stochastic calculus) with the help of some language such as R/Python in order to look at ways to analyze the "stock market". I understand that each term is in itself a wealth of information, but if someone could either direct me towards papers or any literature so that I could refer to what is being done in the field at the current time.

Ideally, I'd like my project to consist of a mathematical content corresponding to that of an advanced undergraduate/beginning graduate student and involve techniques from machine learning to analyse the data sets. The project itself need not be a testament of originality, but anything, even expository is fine.

Sorry for the babble, and I wish you all a good day. Thank you.

~ Always.

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  • $\begingroup$ Brownian motion and Stochastic calculus is widely used in pricing options and other derivatives, so there is a great amount of literature on this. I am not sure what you mean by "ANALYZE THE STOCK MARKET"...that could mean so many different things $\endgroup$ – Dashi Oct 16 '17 at 16:08
  • $\begingroup$ @Dashi Hi - thanks for your response. I meant using the prescribed techniques in order to potentially predict to some accuracy what the future prices may be within a given error? Forgive me if my statements are either vague or foolish. $\endgroup$ – AlwaysNeedHelp Oct 16 '17 at 16:18
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One very good starting book that includes a lot of information on general pricing models as well as stochastic models is:

  1. Options, Futures, and Other Derivatives by John C. Hull
  2. Introduction to Quantitative Methods for Financial Markets by Albrecher, Binder et al.

These are good books that will give you a general outline of how the Browninan motion and Stochastic Calculus is used in pricing financial derivatives.

There is also a lot of other good literature out there, these two are good IMO

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I think I know what you are after, having crossed that bridge myself. Analyzing the stock market is an interesting thing of itself but tread carefully before you think you have a model that will try and predict the stock prices. Here is a large document that talks about modelling high frequency trades. That said, its also a great opportunity to learn time series modeling, probability theory and pattern recognition. Those skills will help you regardless. Here is a collection of books you could buy from. Hope that helps

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