What Are Borel Spaces and Sigma Algebras in Stochastic Calculus for Finance?

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Discussion Overview

The discussion revolves around the concepts of Borel spaces and sigma algebras within the context of stochastic calculus and finance. Participants are exploring the mathematical foundations necessary for understanding these topics, particularly in preparation for interviews at finance firms.

Discussion Character

  • Exploratory
  • Technical explanation
  • Homework-related

Main Points Raised

  • One participant inquires about the mathematical subjects that encompass Borel spaces and sigma algebras, seeking recommendations for relevant literature.
  • Another participant suggests that these topics fall under measure theory and probability, and mentions the availability of free introductory materials online.
  • A different participant emphasizes the importance of understanding stochastic differential equations (SDEs) and Ito's lemma for finance interviews, while also suggesting familiarity with Markov processes and basic statistics.
  • One participant expresses curiosity about the relevance of their background in graph theory to finance, questioning the applicability of their self-studying efforts in the field.
  • A participant shares their experience of completing a PhD in physics and notes that self-studying has been beneficial for some, although they have not yet seen personal success from it.

Areas of Agreement / Disagreement

Participants generally agree on the importance of foundational mathematical knowledge for finance interviews, but there are varying opinions on the relevance of specific mathematical backgrounds and self-study experiences. The discussion does not reach a consensus on the best approach to prepare for interviews.

Contextual Notes

Some participants express uncertainty about how their specific mathematical backgrounds will be perceived in finance roles, and there is a lack of clarity on the direct applicability of certain mathematical concepts to interview scenarios.

Who May Find This Useful

Individuals preparing for finance interviews, particularly those with a focus on stochastic calculus, measure theory, and related mathematical concepts.

Iforgot
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Hey,

I'm studying for interviews at the big finance firms, where I hear they grill you on stochastic calculus and finance stuff.

I'm currently studying Oksendal and Shreve, and while I can follow the applied math parts, I would like to get a firmer grasp on the pure math parts. Does anyone know what subject Borel spaces and sigma algebras fall under, and recommend any books on the subject.

Iforgot
 
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Measure theory and probability. There are lots of free introductory materials online waiting for you to google.
 
Iforgot said:
I'm studying for interviews at the big finance firms, where I hear they grill you on stochastic calculus and finance stuff.

Yes and no. If you don't have deep background on SDE's, then they are likely to see if you know what Ito's lemma is and then grill you on whatever you did your Ph.D. research on.

Something I'd read up on is measure theory and maybe something on markov processes. Also, if you are a physics geek, then it might help if you read up on some very basic statistics and econometrics.

The other thing that will help you is the format of the interview. What will happen is that you will be asked increasingly difficult questions until you get to something that you don't know. What people are interested in seeing is both the limit of your knowledge, but also how you react when you hit your limits.
 
Iforgot said:
Hey,

I'm studying for interviews at the big finance firms, where I hear they grill you on stochastic calculus and finance stuff.

I'm currently studying Oksendal and Shreve, and while I can follow the applied math parts, I would like to get a firmer grasp on the pure math parts. Does anyone know what subject Borel spaces and sigma algebras fall under, and recommend any books on the subject.

Hi there, Iforgot.

I do not want to hijack your thread but I am curious to know how you are finding those textbooks? My expertise is in graph theory - when I began considering jobs in finance I had thought this would serve me well, now I don't really think so. Graph theory is math, but it isn't really complicated. I am not sure how much my applications in data mining will help.. May I ask where your own background lies? I wonder how much self-studying will be 'accepted' - obviously I am taking a similar approach to you and learning whatever I can about related topics, I just hope not using this material in a professional capacity will pose no disadvantage.

Good luck with any interviews.


Neil.
 
It's ok to hijack. I'll forgive you.

I found these textbooks through friends in my program, who found out through their connections.

I just finished my PhD in physics.

Accepted self studying: I've seen it take people a long way. Personally, I haven't taken it anywhere yet.
 

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