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I am a Pure Maths PhD. As I would like to break into quantitative researcher jobs after graduation, I need to pick up statistics, programming and quantitative finance finance.

I have been reading time series analysis by Hamilton and Box Jenkins et al. Also, statistics and Data Analysis for Financial Engineering by Ruppert and Matterson.

I think I need to improve on my statistics background. So may I know what statistics books should I use that have applications in finance?

Idonknow
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    Hi: if you're reading hamilton's text and can follow it, then there's no need for you to get a statistics book. OTOH, by statistics book, do you mean a mathematical statistics text or a linear models-regression type text or a multivariate statistics text ? – mlofton Aug 06 '19 at 03:03
  • Maybe all of them? Actually I am not sure what can be applied in quantitative finance. As long as it can be applied in quantitative finance, then I am interested to learn it. . – Idonknow Aug 06 '19 at 03:16
  • I believe cointegration is not covered in Hamilton's text but it is widely used in quantitative finance, especially algorithmic trading. – Idonknow Aug 06 '19 at 05:03
  • I think my interest is more towards to Statistical analysis in quantitative finance. – Idonknow Aug 06 '19 at 05:07
  • Do you think that my question is better suited to quantitative finance stack exchange? – Idonknow Aug 06 '19 at 05:13
  • Hi: I don't know statistics books that are also quant finance. your best bet is to look at time series- finance texts or econometrics texts. you could sent to quant finance but cross posting is frowned upon so it's best to start a new question. co- integration is definitely covered in hamilton. – mlofton Aug 06 '19 at 22:15
  • get CFA level 1, nothing will be more useful than this – Aksakal Jun 17 '20 at 15:30
  • @Aksakal I agree with you if my financial situation allows it. – Idonknow Jun 17 '20 at 15:37
  • This post might be useful: Introduction to statistics for mathematicians – kjetil b halvorsen Oct 24 '22 at 21:21

2 Answers2

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  1. David Ruppert, David S. Matteson Statistics and Data Analysis for Financial Engineering: with R examples covers some useful models for QF, both in the sense of time series analysis (e.g. GARCH) and the sense of assessing the values of firms (e.g. Fama-French).
  2. Marcos Lopez de Prado Advances in Financial Machine Learning is basically a treasure map if you happen to have tens of millions of dollars to invest in building a QF trading house.
Sycorax
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While not exclusively about finance, these two books cover important applications and statistical concepts :

  1. Essentials of Stochastic Processes.
  2. An Introduction to Statistical Learning.
Trusky
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